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61

NMR ౾࿨ճʤ2022ʥ
ʥ୊ 61 յ

The 61st Annual Meeting of the Nuclear Magnetic Resonance Society of Japan(2022)
ߪԍགྷࢭॄ
Abstracts
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                                       ճ ‫غ‬ʁ2022 ೧ 11 ݆ 8 ೖʤՒʥʛ10 ೖʤ໨ʥNovember 8 – 10, 2022ճ ৖ʁ߶எ‫ݟཱིݟ‬຿ชԿϙʖϩ

二〇二二Kochi Prefectural Culture Hall
ˡ780-0870 ߶எ‫߶ݟ‬எࢤຌௌ 4 ஺໪ 3 Ř 30                                     
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क ࠷ʁೖຌ֫ࣕ‫ڠـ‬໒ָճ高‫࠷ڠ‬ʀ‫࢏ڢ‬ʀ‫ޛ‬ԋʁ߶෾ࢢָճɼೖຌࣕ‫ڠـ‬໒ҫָճɼೖຌਫ਼෼෼ཀྵָճɼ

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知

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෾ࢢՌָճɼೖຌ෾ੵԿָճɼೖຌਫ਼ԿָճɼೖຌࡒྋՌָճɼ

‫ݽ‬ର 105ʀࡒྋϓΧʖϧϞɼఈྖ 105 έϧϔ

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                                      ୊  յ 105 ౾࿨ճ ϕϫήϧϞҗҽճ
ࢃీ

࿪ඛ

ʤ߶எ୉ָʥ   ʨҗҽௗʩ‫ ࣄݚ‬भ߄ʤಛౣ୉ָʥ ʨοϣʖφϨΠϩ୴౲ʩ

ӊघ 

ߔҲ

ʤಛౣ୉ָʥ

୉໨ೞʤ෼࣯ʀࡒྋ‫ߑؽڂݜ‬ʥ ʨण෉୴౲ʩ

‫ޛ‬౽

࿪ഇ

ʤԮࢃ୉ָʥᤶ‫ݛ‬ӋʤԮࢃ୉ָʥ㒖ਇҲʤ߁ౣ୉ָʥ

஧ଞ߶ࢦʤཀྵԿָ‫ॶڂݜ‬ʥ   ʨࠛ਎ճ୴౲ʩ

҈ీ

‫ڭ‬୉

ʤ߁ౣ୉ָʥ                                       ճ৖ʤ߶எ‫ݟཱིݟ‬຿ชԿϙʖϩʥ΃͹ި௪Ҍ಼ ߶எ‫ݟཱིݟ‬຿ชԿϙʖϩϩ
.RFKL3UHIHFWXUDO&XOWXUH+DOOˡ ߶எ‫߶ݟ‬எࢤຌௌ  ஺໪  Ř ߦ‫ؽۯ‬Ν͟ཤ༽͹৖߻߶எྀഇ‫͖ߕۯ‬Δ νέεʖͲ༁  ෾‫ߕۯ‬࿊ཙώηʤ‫ݟ‬ு઴ߨ͘ʥʽ༁  ෾ʾʰ‫ݟ‬ு઴ʱԾऄ ైิ਼෾‫ߕۯ‬࿊ཙώηʤ-5 ߶எӼߨ͘ʥʽ༁  ෾ʾʰͺΕΉΏ‫ڰ‬ʱԾऄɽͳ͠ͲΞި௪࿑໚ుऄʤ‫ں‬ઔ‫ڰ‬ɼ௉૖ɼ͏͹๏໚ʥͶ৒Ε‫͓׷‬ʽ༁  ෾ʾʰ‫ݟ‬ு઴ʱԾऄ ైิ਼෾ʽ‫ߕۯ‬࿊ཙώη͹৆ࡋʾ
KWWSZZZNRFKLDSFRMSDFFHVVEXV ΍͚͢ͺʰ߶எྀഇ‫ ߕۯ‬࿊ཙώηʱͲ‫ࡩݗ‬-5 Ν͟ཤ༽͹৖߻߻
-5 ߶எӼ͖Δ νέεʖͲ༁  ෾ɼైิͲ‫ئ‬௃Ηͻ༁  ෾ͳ͠ͲΞި௪࿑໚ుऄʰ߶எӼ઴ʱʽ༁  ෾ʾʰͺΕΉΏ‫ڰ‬ʱԾऄɽʰ‫ں‬ઔ‫ڰ‬ɼ௉૖ɼ͏͹๏໚ߨ͘ʱͶ৒Ε‫͓׷‬ʽ༁  ෾ʾʰ‫ݟ‬ு઴ʱԾऄ ైิ਼෾ʽͳ͠ͲΞި௪࿑໚ుऄ͹৆ࡋʾ
KWWSVZZZWRVDGHQFRMSWUDLQURVHQ]XSKS΍͚͢ͺʰͳ͠ͲΞި௪ ుऄ࿑તਦʱͲ‫ࡩݗ‬－1－ ޳ಆ൅නճ৖ʤΨϪϱζϙʖϩʥ͹Ҍ಼ਦ ͳ͠ͲΞި௪ʰ‫ݟ‬ு઴ʱʤࠅಕ  ߺતʥ͖Δైิ ʛ ෾ɽ‫ݒ‬෼ਜ਼໚Ͷ޴͖ͮͱࠪଈ͗ΨϪϱζϙʖϩʤ޳ಆ൅නճ৖ʥ
ɼӊଈ͗ࣆແ౫ʤ ֌ϛηνʖճ৖ʥͲͤɽ
ΨϪϱζϙʖϩϫϑʖͶण෉ͳघࢨভಡʀ‫ݗ‬Իαʖψʖ͍͗ΕΉͤɽ－2－ ϛηνʖճ৖ʤࣆແ౫  ֌ʥ͹Ҍ಼ਦ ϛηνʖճ৖ͺࣆແ౫  ֌Ͳͤɽ޳ಆ൅නճ৖ʤΨϪϱζϙʖϩʥ͖Δ
ͺɼࣆແ౫  ֌ΓΕΦϪϗʖνʖ΍͚͢ͺ֌ஊᶅΝ͟ཤ༽͚ͫ͠͏ɽΦϪϗʖνʖ઴͹ϙʖϩͶघࢨভಡαʖψʖ͍͗ΕΉͤɽΨϪϱζϙʖϩ΃໯ΖͶͺɼΦϪϗʖνʖ΍͚͢ͺ֌ஊᶆΝ͟ཤ༽͚ͫ͠͏ʤືॄյඈ͹ͪΌʥɽ୊Ҳϛηνʖճ৖ʤ3ʛ3 ʥͳ୊್ϛηνʖճ৖ʤ3ʛ3<ʥͶ෾͖Ηͱ͏Ήͤɽ－3－ ೈքφϧϓஏਔ൅ਫ਼࣎͹ଲԢͶͯ͏ͱ ೈքφϧϓஏਔͺɼ֕͸ ʛ ೧ֶؔͲ‫܃‬Εศ͢൅ਫ਼͢ͱ͕Εɼ઴յ͹ೈքφϧϓஏਔʤদ࿪౨ೈ
քஏਔʤ ೧ʥ‫;ٶ‬দ࿪ೈքஏਔʤ ೧ʥʥ͗൅ਫ਼͢ͱ͖Δ  ೧Ґ৏͗‫ܨ‬գͪ͢‫Ͳࡑݳ‬ͺɼ࣏͹ೈքφϧϓஏਔ൅ਫ਼͹઀യ੓͗߶Ήͮͱ͘ͱ͏Ήͤɽ߶எ‫ݟཱིݟ‬຿ชԿϙʖϩͲͺɼ΢ϱνʖϋρφΝ௪ͣͱࣆ‫ंۂ‬ΓΕഓ৶͠ΗΖ߶ౕཤ༽ं޴͜‫ٺە‬ஏਔଐๅૹ஖Νઅ஖͢ͱ͏Ήͤɽ௪৙ɼਔౕ̔ओҐ৏͗༩૟͠ΗΖ৖߻Ͷɼ୉ঘϙʖϩ͹‫ੰٮ‬Ν‫؜‬΋સ‫ؙ‬Ͷඉ৙๎ૻ͗ླྀΗΉͤɽඉ৙๎ૻͺɼ̢̥̟οϡ΢ϞԽ͹‫ޛ‬ͶԽ੢Ͳ͕எΔͦ͢Ήͤɽೈքφϧϓ‫ڌ‬୉ஏਔͲͺɼඉ৙๎ૻ͗ླྀΗͱ͖Δ‫༵͏ک‬Η͚͗ΖΉͲ͹࣎ؔͺΚ͖͖͍ͥ͢ΕΉͦΞɽඉ৙๎ૻ͗ླྀΗͪΔɼ͍ΚͱͥͶਐ͹҈સΝ֮ฯ͢ͱ͚ͫ͠͏ɽ‫ݟ‬຿ชԿϙʖϩͺଳਔ޽ࣆΝߨͮͱ͏Ήͤ͹Ͳɼ‫ܐ‬ҽ͹ࢨࣖͶॊ͏ɼཚͬ஥͏ͱߨಊ͢ͱ͚ͫ͠͏ɽઊଲͶ͍Κͱͱड़޳Ώ֌ஊͶࡶ౺͢͵͏Ͳ͚ͫ͠͏ɽ௣ഀ͗൅ਫ਼͢͵͏ͳ༩૟͠Ηͪ৖߻ͺɼ߁Үඈೋ৖ॶʤ୍ঌޮԄɼ߶எ৕ʥͶඈೋ͢ͱ͚ͫ͠
͏ɽΉͪɼ௣ഀ൅ਫ਼࣎ͺɼࣆແ౫  ֌΍͚͢ͺԲ৏͗ඈೋ৖ॶͳ͵ΕΉͤɽΨϪϱζϙʖϩ͹ඈೋ‫ܨ‬࿑ਦਦ－4－ ৿‫ܗ‬αϫψΤ΢ϩη͹‫״‬ઝ༩๹ଲࡨͶͯ͏ͱ ̏ɿ‫״‬ઝ঳༩๹ଲࡨͳ͢ͱࣰࢬͤΖߴ໪ʀ৿‫ܗ‬αϫψΤ΢ϩηͶ‫״‬ઝ͢ͱ͏Ζٛ͏͹͍Ζ๏͹པ৖ࣙख़͹͕‫͏ب‬ʀΨϪϱζϙʖϩϫϑʖण෉઴Ͷ͕͜Ζ‫ݗ‬Ի͹ࣰࢬʤ֦ೖʥ
ʀճ৖಼Ͳ͹৙࣎Ϝηέ஥༽͹͕‫͏ب‬ʀճ৖಼֦ॶ΃घࢨভಡӹΝઅ஖ʀߪԍճ৖಼͹న઀͵ֶ֮ؔฯ͹͕‫͏ب‬ɼ͕Γ;೘ୂ࣪ϩʖφ͹ࢨఈ౵͹ືॄյඈଲࡨ͹ࣰࢬʀఈ‫غ‬ద͵૯֋͜౵ͶΓΖɼճ৖಼͹‫ـ׷‬͹ྯߨʀϜ΢έɼԍୈɼ3& ંକίʖϔϩ౵ɼճ৖಼͹‫༙ڠ‬෨෾͹ఈ‫غ‬ద͵ভಡʀӁৱ࣎͹໩ৱ౵͹ྯߨʀ୉੢Ώ֑౵͹Φοίρφॳग͹‫͖͜;ݼ‬̐ɿࢂՅΝ༩ఈ͠Ηͱ͏Ζև༹΃͹͕‫͏ب‬ʤ۫ରద͵ࣰࢬߴ໪ʥ ʥ༙঳য়ं͹ࢂՅࣙख़
౾࿨ճճ৖Ͷཔ৖͠ΗΖ઴ͶʤՆ೵͵‫ݸ‬Εʥ֦ࣙͲ‫ݗ‬Ի͢ͱ͏ͪͫ͘ɼରԻ͗ ˈҐ৏͹৖߻ɼ͍Ζ͏ͺ ˈາຮͲ΍ର௒෈ྒྷ͹৖߻ͺཔ৖Ν͟ԗ͚ྂͫ͠͏ɽ͵͕ߪԍ༩ఈ͹๏͹৖߻ͺɼͨ͹ࢭΝ੊࿫ਕΉͲ͟࿊ཙ͚ͫ͠͏ɽ
 ʥण෉࣎Ͷ͕͜Ζ‫ݗ‬Իʤ֦ೖࣰࢬʥ
ΨϪϱζϙʖϩϫϑʖण෉઴Ͷͱ‫ݗ‬ԻΝࣰࢬ͏ͪ͢ΉͤɽରԻ͗ ˈҐ৏͹๏ɼΉͪͺ ˈາຮͲ
͍ͮͱ΍ɼԾ‫ى‬ᶅʛᶇ͹͏ͥΗ͖Ͷ౲ͱͺΉΖ๏͹ࢂՅͺ͕இΕͤΖ৖߻͍͗ΕΉͤ͹Ͳ͟྅ট͚ͫ͠
͏ɽᶅଋ‫͢͠ۦ‬Ώ‫ͫ͏ک‬Ζ͠ɼ͹ʹ͹௩Ίɼ߶೦͹͏ͥΗ͖͹঳য়͍͗ΖɽᶆർֳదܲඏͲ͍ͮͱ΍ɼ൅೦Ώ֑͵ʹ͹෫इ঳য়ΏັְΏᅁְ͹ҡ৙͍͗Ζɽ
ᶇ໎Δ͖Ͷର௒෈ྒྷͨ͑Ͷ‫͓ݡ‬Ζ͗ɼ౲ೖ൅න͍͗Ζ͹Ͳըອ͢ͱ͏Ζ๏ ʥϜηέ͹৙࣎஥༽͹͕‫͏ب‬౾࿨ճ‫ؔغ‬஦ɼ‫ݬ‬ଉͳ͢ͱճ৖಼Ͳͺ৙࣎Ϝηέʤ෈৭ා੣ΝਬওʥΝਜ਼͚͢஥༽͢ͱ͏ͪͫ͘ΉͤΓ͕͑‫ͪ͢͏͏ب‬Ήͤɽ஥༽͏ͪͫ͜͵͏৖߻ͺࢂՅΝ͕இΕͤΖ৖߻͗͟͡͏Ήͤ͹Ͳɼ༩Ό͟྅ট͚ͫ
͠͏ɽΉͪɼ౾࿨ճηνρϓ΍৙࣎ϜηέΝ஥༽͢ͱ͕ΕΉͤ͹Ͳɼญͦͱ͟྅ট͚ͫ͠͏ɽ
 ʥճ৖಼Ͷ͕͜Ζࢀືʤືถʀືॄʀືંʥյඈ
޳ಆ൅නճ৖ʤΨϪϱζϙʖϩʥͲͺన઀͵‫཯ړ‬Νͳͮͱ஥ੰ͚ͫ͠͏ɽճ৖಼Ͳͺड़೘޳͹ࢨఈ౵ɼಊ
તΝ੏‫͏ͱ͢ݸ‬Ζ৖߻͍͗ΕΉͤɽճ৖‫ܐ‬͹ࢨࣖͶॊͮͱ͚ͫ͠͏ɽͨ͹ଠɼճ৖಼Ͳ͹λʖεϡϩυΡ
ηνϱη֮ฯͶ͟‫ྙڢ‬Ν͕‫ͪ͢͏͏ب‬Ήͤɽ－5－ʥӁৱ
‫ؔ࣎ܞٵ‬Ͷ‫࣪ܞٵ‬ʤࣆແ౫  ֌ʥΏΨϪϱζϙʖϩϫϑʖͶ͕͏ͱӁৱ͢ͱ͏͚ͪͫ͞ͳͺՆ೵Ͳͤ͗ɼͨ͹ࡏͺɼ໩ৱΉͪͺϜηέճৱΝ͕‫ͪ͢͏͏ب‬Ήͤɽ͵͕ɼϙʖϩ‫Ͳ಼ੰٮ‬͹Ӂৱͺ͟ԗ͚ྂͫ͠͏ɽ ʥͨ͹ଠ
105 Ͷ‫ͤؖ‬Ζപ೦ͪ͢٠࿨ͺ୉‫͗ͤͲܶ׽‬ɼ୉੢Νड़ͤ͞ͳͺ͕߉͓͚ͫ͠͏ɽճ৖֐Ͷ͕͏ͱ΍ࠅɼ߶எ‫ݟ‬ɼ֦ॶ଒ૌ৭͹ϩʖϩͶॊ͏ɼ‫״‬ઝ༩๹Νৼֽ͜ͱ͏ͪͫ͘ΉͤΓ͕͑‫ͪ͢͏͏ب‬Ήͤɽ౾࿨ճճ
‫غ‬஦͕Γ;श྅‫  ޛ‬ೖҐ಼Ͷɼ৿‫ܗ‬αϫψΤ΢ϩηཇ੓ͳਏஇ͠Ηͪ৖߻ͺɼଐΏ͖Ͷ੊࿫ਕΉͲ͟࿊ཙ͚ͫ͠͏ɽΉͪɼ౾࿨ճճ‫غ‬஦Ͷɼ৿‫ܗ‬αϫψΤ΢ϩηཇ੓ͳਏஇ͠Ηͪ๏͗ࢂՅ͠Ηͱ͏ͪࣆ֮͗೟
͠Ηͪ৖߻ɼͨ͹‫ޛ‬͹ೖఖΝ஦ࢯͤΖ৖߻͍͗ΕΉͤɽҐ৏ɼ͟෈สʀ͟໐࿯Ν͕͖͜͏ͪ͢Ήͤ͗ɼ৿‫ܗ‬αϫψΤ΢ϩη‫״‬ઝ঳֨୉๹ࢯ͹ͪΌ͟ཀྵմ͟‫ྙڢ‬͹ΆʹΓΘ͚͕͢‫͏ب‬ਅ͢৏͝Ήͤɽ
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－6－

 ୊  յ 105 ౾࿨ճʤʥೖఖන －7－ ࢂՅं΃͹͟Ҍ಼ ɿण෉ͳࢂՅౌ࿧ण෉ͺΨϪϱζϙʖϩϫϑʖͶઅ͜Ήͤɽण෉࣎ؔʁ ݆  ೖʤՒʥ ʁʛʁ ݆  ೖʤਭʥ ʁʛʁ ݆  ೖʤ໨ʥʁʛʁ

ʀࣆ઴ౌ࿧ΝࡃΉͦɼࢂՅඇΝࢩ෹͏ࡃΊ͹๏ͺɼण෉υηέͲघକ͘Νߨ͑චགྷͺ͍ΕΉͦΞɽຌགྷࢭॄͶಋ෩ͪ͢ࢂՅৄΝ఑ࣖ͢ͱ͏͚ͪͫͫ͜Ͳ͟೘৖Ͳ͘ΉͤɽࢂՅৄϙϩξʖͺճ৖೘޳෉ۛͶ஖͏ͱ͍ΕΉͤ͹Ͳɼࣙ͟༟Ͷ͕࢘͏͚ͫ͠͏ɽճ‫غ‬஦ͺࢂՅৄϙϩξʖ͹஥༽Ν͕‫ͪ͢͏͏ب‬Ήͤɽʀࣆ઴ౌ࿧ΝࡃΉͦͱ΍ɼࢂՅඇ͹৾ΕࠒΊ֮͗೟Ͳ͘͵͖ͮͪ๏ͺɼ౲ೖࢂՅౌ࿧ѽ͏ͳ͵ΕΉͤɽʀ౲ೖࢂՅ͹๏ͺɼण෉઴Ͷ஖͖Ηͪ౲ೖࢂՅं༽༽ࢶͶචགྷࣆߴΝ͟‫ى‬೘͹৏ɼण෉υηέΉͲ͕ӿ͚ͫ͢͠͏ɽࢂՅඇΝ‫ࢩ͕Ͳۜݳ‬෹͏͏ͪͫ͘Ήͤɽ͕ోͤ͢ΖࢂՅৄͶॶ଒ͳࢱ໌Ν֦ࣙͲ‫ى‬೘͢ɼճ৖಼Ͳ஥༽͢ͱ͚ͫ͠͏ɽ
౲ೖࢂՅ౾࿨ճࢂՅඇ

ճҽ

ඉճҽ

ਜ਼ճҽ

ָਫ਼ճҽ

Ҳൢ

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 ԃ ԃ ԃ ԃʀ྘फॽ͹൅ߨ
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ຌߪԍགྷࢭॄͺɼೖຌ֫ࣕ‫ڠـ‬໒ָճճҽͳࣆ઴ࢂՅౌ࿧Νͪ͢ඉճҽʤҲൢʀָਫ਼ʥͶࣆ઴ૻ෉͢ͱ͕ΕΉͤɽ࢔෨͍͗Ζ৖߻Ͷ‫ݸ‬ΕɼҲ࡯Ͷͯ͘  ԃͲ౲ೖ൤ജΝߨ͏Ήͤɽʀָճඇ͹ࢩ෹͏ͳ೘ճघକ͘
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ˡ ߶எ‫߶ݟ‬எࢤຌௌ  ஺໪  Ř ߶எ‫ݟཱིݟ‬຿ชԿϙʖϩ ΨϪϱζϙʖϩϫϑʖʀճ‫֐غ‬୊  յ 105 ౾࿨ճˡ ߶எ‫ݟ‬ೈࠅࢤԮ๝ௌঘ࿉
߶எ୉ָԮ๝ΫϡϱϏηҫָ෨૱߻‫ڂݜ‬౫ ,,, ߺ࣪7HOʁ ൅නं΃͹͟Ҍ಼ʀ࠴ௗ͹๏΃࠴ௗ͹๏ͺɼ୴౲ιρεϥϱͶ͵ΕΉͪ͢ΔɼηέϨʖϱ޴͖ͮͱӊଈ͹࠴ௗੰʤஅ৏ʥΉͲ͕ӿ͚ͫ͢͠͏ɽ਒ߨͺસͱ࠴ௗͶҲ೜͏ͪ͢ΉͤɽՀͶιρεϥϱश྅࣎ؔ͗Ψʖώʖͪ͢৖߻ͺɼ௜‫ޛ‬͹‫ؔ࣎ܞٵ‬Ν୻क़͢ɼϕϫήϧϞ௪ΕͶ࣏͹ιρεϥϱΝ࢟Όͱ͚ͫ͠͏ɽΉͪɼ࣏͹ιρεϥϱ֋࢟࣎ࠃΝճ৖ͶΠψΤϱη͢ͱ͚ͫ͠͏ɽ৿‫ܗ‬αϫψΤ΢ϩη‫״‬ઝ༩๹͹ͪΌɼϜ΢έϏʖλϱΝഓ஖ͦͥɼ ຌ͹࣯໲ं༽Ϝ΢έΝ௪࿑Ͷ༽қ͏ͪ͢Ήͤɽ࣯ٛԢ౶࣎ؔͶ͕͏ͱ࣯໲Ώαϟϱφ͍͗Ζ৖߻ͺɼ࣯໲ं͗ۛ๥͹Ϝ΢έΉͲ͕ӿ͢Ͷ͵ΖΓ͕͑ఽ͓͚ͫ͠͏ɽ
ʀ޳ಆ൅නं͹๏΃൅නͺ൅නंࣙਐ͹ 3& Ͳߨͮͱ͏ͪͫ͘Ήͤ͹Ͳɼචͥ࣍͟ࢂԾ͠͏ɽӹধϕϫζΥένͺʤঙ͢೧‫ل‬͹೘ͮͪ඾෼Ͳͤ͗ʥճ৖͹ඍ඾Ν࢘༽͢Ήͤɽόʖφ 3& ͳ͹ંକ༽ͳ͢ͱ +'0,ίʖϔϩͳ 9*$ ίʖϔϩΝ༽қ͏ͪ͢Ήͤʤ9*$ ͹Ϝηνʖίʖϔϩ͖Δร‫ؽ׷‬Ν௪ͣͱྈίʖϔϩͳંକ͢Ήͤɽʥ
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͏ɽ૤ࡠͶͯ͏ͱ෈໎͵఼͍͗Ζ৖߻ͺɼճ৖୴౲ηνρϓͶ͟૮஌Ծ͠͏ʤ৏घ͚ߨ͖͵͏৖߻ͺɼճ৖͹ӹধϕϫζΥένʤ9*$ʥͶ௜ંંକͤΖ͖ɼճ৖͹ 3&ʤ:LQGRZVʥΝ࢘༽͢Ήͤɽʥɽ൅නυʖνΝ 86% ϟϠϨ౵Ͷ೘ΗͱɼώρέΠρϕ༽ͳ͢ͱ࣍͟ࢂ͚ͫ͠͏ɽώρτϨʖ઀ΗͶඍ͓ͱɼචͥు‫ݱ‬ΠξϕνʖΝ࣍ࢂ͢ͱ͚ͫ͠͏ɽϪʖδʖϛ΢ϱνͺճ৖Ͷ༽қ͠Ηͱ͕ΕΉͤɽߪԍ࣎ؔͺɼಝพߪԍ  ෾ɼডଶߪԍ  ෾ɼҲൢߪԍ  ෾ͲͤɽԾ‫ى‬͹ν΢ϝϱήͲɼϗϩΝ໒Δ͢Ήͤɽ಼࣍ͬ࣎ؔͲ͹श྅Ͷ͟‫ͫͪ͜͏ྙڢ‬ΉͤΓ͕͑‫ͪ͢͏͏ب‬Ήͤɽ൅නश྅‫ޛ‬－9－ͺɼͤΊΏ͖Ͷ࣏͹൅නंͳިେ͢ͱԾ͠͏ɽ
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͵͕ɼಝพߪԍͶͺ࣯ٛ͹࣎ؔͺ͟͡͏ΉͦΞɽʀϛηνʖ൅නं͹๏΃ϛηνʖ൅නͶ͕͜Ζ࢘༽‫ޢݶ‬ͺɼӵ‫ޢ‬΍͚͢ͺೖຌ‫ͪ͢͏ͳޢ‬Ήͤɽ‫ंޛ‬͹৖߻ɼӵ‫ޢ‬ͶΓΖν΢φϩʀ໌઴ʀॶ଒΍ญ‫͏͚ͫ͠ͱ͢ى‬ɽΉͪɼ൅නं͹ࢱ໌ͶͺʕһΝ෉͜ͱ͚ͫ͠͏ɽช
࣊Ώਦ͹୉͘͠ɼߨؔͶͯ͏ͱͺɼΏΏ཯Ηͪ‫͖཯ړ‬ΔͲ΍൓พͲ͘ΖΓ͑ͶഓྂΝ͕‫ͪ͏͏ب‬͢ΉͤɽϛηνʖϚʖχ͹୉͘͠ͺ ॐ FPʹ ԥ FP Ͳͤɽজ͖Δ FP ఖౕ͹ηϘʖηΝ‫ͳ͚͕͞ͱ͜ۯ‬Νਬও͢Ήͤɽժයͺ֦ϛηνʖϏϋϩͶ༽қ͏ͪ͢Ήͤɽࠪ৏۳ FP
࢝๏͹ηϘʖηͶԍୌ൬ߺΝනࣖ͢ͱ͕ΕΉͤ͹Ͳɼ֦ࣙ͹ϏϋϩͶ‫ͱࣖ͢ܟ‬Ծ͠͏ɽϛηνʖճ৖ͺࣆແ౫  ֌͹୊Ҳϛηνʖճ৖ʤ୊  ଡ໪ద࣪ʥͳ୊್ϛηνʖճ৖ʤ୊ ʀ ଡ໪ద࣪ʥ
Ͷ෾͖Ηͱ͕ΕΉͤɽ઴ߴʰϛηνʖճ৖ʤࣆແ౫  ֌ʥ͹Ҍ಼ਦʱΝ͟ࢂল͚ͫ͠͏ɽ౲ॵɼ
୊್ϛηνʖճ৖ͺౖଏ‫͕ͱ͓͢ఽ͕ͳࢯے‬ΕΉͪ͗͢ɼ཈ਫ਼ͤΖ͞ͳͶ͵ΕΉͪ͢ɽηϨρϏ͵ʹས෼͹࣍͟ࢂͺ෈གྷͳ͵ΕΉͤɽϛηνʖ൬ߺ͗۰਼൬ߺ͕Γ;ऑघϛηνʖৈޫึ͹๏
ʤ33 ʀʀʀʥͺɼ ݆  ೖʤՒʥ ʁʛʁ Ͷϛηνʖ౾࿨ΝߨͮͱԾ͠͏ɽऑ
घϛηνʖৈޫึͶ͕͜Ζϛηνʖ൬ߺ͹຦ඎͶͺʰ<ʱ͗ͯ͏ͱ͏Ήͤɽ‫਼د‬൬ߺʤ33ʀʀʀʥ͹๏ͺɼ ݆  ೖʤ໨ʥ ʁʛʁ Ͷϛηνʖ౾࿨ΝߨͮͱԾ͠͏ɽ൅න࣎ؔ͹ؔͺɼචͥϛηνʖ઴Ͷཱིͬɼ࣯໲ͳ౾࿨ͶԢͣͱԾ͠͏ɽճ‫غ‬஦ͺϛηνʖ͹௃Ε଺͓Νߨ͏ΉͦΞɽસͱ͹൅නϛηνʖͺ  ݆  ೖʤՒʥ ʁʛʁ ͹ؔͶ‫ࣖ͢ܟ‬ɼ ݆  ೖʤ໨ʥ
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৖ ॶʁ߶எ‫ݟཱིݟ‬຿ชԿϙʖϩʀΨϪϱζϙʖϩೖຌ֫ࣕ‫ڠـ‬໒ָճ૱ճΝ৏‫ى‬ೖఖͲ֋࠷͏ͪ͢Ήͤɽճҽ͹๏ͺචͥ͟ड़ੰ͚ͫ͠͏ɽΏ΋Νಚͥܿੰ͠ΗΖ๏ͺࣆ઴Ͷҗ೜য়͹఑ड़Ν͕‫ͪ͢͏͏ب‬Ήͤɽҗ೜য়ͺ 105 ωϣʖηϪνʖͲૻ෉͠ΗΉͤɽҗ೜য়Ͷ͟‫ى‬೘͹৏ɼࢨఈ͹఑ड़઎ͶϟʖϩͲૻ৶Ν͕‫ͪ͢͏͏ب‬Ήͤɽࢶഖର͹җ೜য়Ν౲౾࿨ճ͹ण෉Ͷ΍༽қ͢ͱ͕ΕΉͤ͹ͲɼϟʖϩͲ఑ड़͢͵͖ͮͪ๏ͺɼ૱ճ֋࢟ΉͲͶण෉ΉͲ͟఑ड़͚ͫ͠͏ɽ͵͕ɼҗ೜য়͹఑ड़ͺɼ૱ճΝܿੰͤΖҲൢճҽͫ͗͜චགྷ
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－ 11 － οϣʖφϨΠϩαʖη ೖ ࣎ʁ ೧  ݆  ೖʤ݆ʥ ʛ ʤण෉ ʛʥճ ৖ʁ߶எ‫ݟཱིݟ‬຿ชԿϙʖϩʀΨϪϱζϙʖϩ ʤण෉ʁΨϪϱζϙʖϩϫϑʖʥʤ̏ʥʁʛʁ

$; ηϒϱ‫ܧ‬ͺ༃෾͖Δ͵͏͜ʹɼΏͺΕʰϟοϩ‫خ‬ʱ༹༹ஓ৏ ‫ ٳي‬઎ਫ਼ ʤԥශࢤཱི୉ָʥ༻ӹ 105 Ͷ‫Ͳͳͪͮ͞ݸ‬ͺ͵͏͗ɼՁ͖γϱϕϩ͹ +&105 Ν଎ఈͤΖͳɼ༻ഖ͹ϒʖέΝঈ͏ͱਇͮ઎Ͷ໪Ͷඊ;ࠒΞͲ͚Ζ͹ͺϟοϩ‫خ‬͹ϒʖέͲͺ͵͏ͫΘ͖͑ʃεϡʖϕͲҲࡏ߶͚ͨ;ཱི͓ͯϒʖέΝ‫ݡ‬Ζͳɼঙ͵͚ͳ΍γϱϕϩ͗༻͜ͱ͏ͪ͞ͳͶϙρͳҲ҈ৼͤΖ͹ͺජंͫ͜Ͳͺ͵͖Θ͑ɽ͞Ηͺఁ෾ࢢͫ͜Ͳ͵͚߶෾ࢢ͹৖߻Ͳ΍ಋͣͲɼಝͶ஁പ 105 ͹෾໼Ͳͺ෾ࢢྖ͗  ຬΝ௔͓ΖวΕ͖Δɼ͞ΗΉͲ͹ +1 Πϝχ‫Ͳخ‬ͺ͵͚ɼ+& ϟοϩ‫͗خ‬कༀͶ༄Εड़ͪɽࠕͲͺࢾྋࡠΕ΍଎ఈ๑΍͖͵ΕϩʖοϱԿ͠Ηͱ͏Ζ͗ɼ΀ͳɼʰՁ‫ބ‬ϟοϩ‫خ‬ͺͨΗΆʹ‫͚߶ౕ͗״‬ɼ0'D ϪϗϩͲ΍؏଎Ն೵͵͹͖ʃʱͳ͏఼͑͗‫ـ‬Ͷ͵Ζ͞ͳ͍͗ΖɽʰͨΗͺ΍ͬΘΞ + ϒʖέ͗  ͯ΍॑͵
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ϫζρέ͗ࣇͱ͏ΖɽʀτϱλϩͮͱՁʃ
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‫ܯ‬଎घ๑ͳ͢ͱ͹ 05, Νʹ͹Γ͑Ͷ࢘ͮͱ͏͚͖ഊࢥ ஒ೯ ઎ਫ਼ ʤࠅࡏҫྏෳࢳ୉ָʥ
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－ 13 －

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－ 14 －୊  յ 105 ౾࿨ճʤʥ
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Kochi Prefectural Culture Hall
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－ 15 －

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৙ࣕ੓ &H) ͹ϓρԿ෼΢Ψϱఽ಍͹‫ݽ‬ର 105 մੵ˕ଞ৏ ඔ࿪  ɼྰ॑ Ի  ‫౐ښ‬୉ָࢊ‫ָׯ‬࿊‫ܠ‬ຌ෨ɼ ฎ‫ཱིݟށ‬୉ָ୉ָӅ޽ָ‫ڂݜ‬Ռ
/‫ݽ‬ର 105 ͶΓΖ༙‫( ؽ‬/ ൅ޭࡒྋ͹ఈྖదඉধߑଆմੵ˕ׁ ߄ఱ  ɼྵ໨ ࠂ໎  ‫౐ښ‬୉ָԿָ‫ॶڂݜ‬  ‫ܞٵ‬ʙ%UHDNWLPH
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/ਫ਼ରࢾྋ͹୐৏ 105 ૹ஖ͶΓΖ෾ੵघ๑͹‫ݗ‬౾˕૮ୖ ஒ߃  ɼ૛ ࢢ߿  ɼ‫ ؃‬ᣨ  ɼি Մ‫  م‬ɼ‫ ދ‬எඛ  ɼ୉੤ ༡‫  ل‬ɼௗీ ੥࢚  ɼ‫ٳ‬ธీ ദ೯  ɼ‫ۿ‬໨ ߃༡  ɼࢃ಼ Ҳ෋  ๼քಕ୉ָ୉ָӅ઎୼ਫ਼ໍՌָ‫ڂݜ‬Ӆɼ ஦ࢃঐࣆ‫ࣞה‬ճऀɼ ԯೆՌָٗढ़୉ָӅ୉ָ‫حؽ‬෾ੵιέεϥϱ－ 24 －

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105 մੵΝ༽͏ͪմ౸‫߮ܧ‬ો 3*. ͹‫ڧ؂‬నԢద‫׈‬੓੏‫ޜ‬ͶΓΖմ౸‫ܧ‬௒ઇ‫ߑؽ‬˕ൂ໨ ޼থ  ɼᷦ੤ ୐ຑ  ɼ(OLVD5LRXDO ɼஓ୫ రฎ  ɼ໨ઔ ཾଉ  ཀྵԿָ‫ॶڂݜ‬ਫ਼ໍ‫ؽ‬೵Ռָ‫ڂݜ‬ιϱνʖɼ ౨‫ཱི౐ښ‬୉ָཀྵָ෨

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－ 25 －    ϛηνʖ൅නʙ3RVWHUSUHVHQWDWLRQ    ճ৖ʁࣆແ౫  ֌ϛηνʖ൬ߺ 3ʛ3ʁ ୊Ҳϛηνʖճ৖ʤ୊  ଡ໪ద࣪ʥ

ϛηνʖ൬ߺ 3ʛ3<ʁ୊್ϛηνʖճ৖ʤ୊  ଡ໪ద࣪ʥ

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ʤ۰਼൬ߺ͹຦ඎ̰ʁऑघϛηνʖৈΦϱφϨʖʥϛηνʖ‫ࣖܟ‬ʁ  ݆  ೖ t

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% ‫ܗ‬،ԎΤ΢ϩη ; ஁പ࣯ʤ+%[ʥ͹ & ຦ଈܿࣨรҡରϘϕοχͳ߇Πϛφʖεη஁പ࣯ %FO[/ ͹૮‫༽ࡠޕ‬͹ 105 մੵ˕೉ ӵध  ɼࡖຌ ଻Ҳ  ɼՑ໼ य़೯  ɼऑন ֞  ɼශ޳ ޯ  ɼӮీ ਺  ࠅཱི‫״‬ઝ঳‫੊࣏ॶڂݜ‬େਫ਼෼ָద੣ࡐ‫ڂݜ‬ιϱνʖɼ એཁ޽‫ۂ‬୉ָ઎਒޽ָ෨ɼ ๼཮୉ָҫָ෨ɼ ‫܊‬ഇ୉ָ୉ָӅཀྵ޽ָැɼ ‫౐ښ‬୉ָΦϋϩάʖཀྵ޽ָ‫ॶڂݜ‬3<ϓϩΨϫΫόϫϱԿ߻෼ͳ 51$ ͳ͹૮‫༽ࡠޕ‬մੵʁۛંͤΖԚ‫خ‬ଲ͹Ӫ‫ڻ‬͹մੵ˕Ҳᑏ ཨ՘  ɼ৏ଞ ޻  ɼՑ߻ ߸ଢ  એཁ޽‫ۂ‬୉ָɼ ‫ࣞה‬ճऀ 9HULWDV,Q6LOLFR3ਭ༻ӹࢾྋͶ͕͜Ζ 3XUH6KLIW ଎ఈ͹ࢾΊ˕߶‫ڰ‬੒ࢀ  ɼՑ߻ ߸ଢ  એཁ޽‫ۂ‬୉ָ୉ָӅਫ਼ໍՌָ‫ڂݜ‬Ռ
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ร௒ͪ͢Ϝ΢έϫഀΝ༽͏ͪಊద֫ย‫ིްۅ‬͹޴৏˕௃ ஧ྒྷ  ɼ ন໨ ཇ   ɼ ౽‫ ݬ‬ෆಕ   ୉ࡗ୉ָ஁പ࣯‫ॶڂݜ‬ɼ ୉ࡗ୉ָྖࢢ৚ๅʀྖࢢਫ਼ໍ‫ڂݜ‬ιϱνʖ3ࣕ৖ૡӀ 6:,)7 ͶΓΖ  ࣏‫ ݫ‬05,
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෾ࢢࠒΊ߻͏‫ڧ؂‬ԾͶ͕͜Ζ '1$ ࢀ॑࠱ߑଆ͹Ԛ‫خ‬ଲ͹֋ถξ΢ψϝέη͹؉࿪෾ࢆ๑Ν༽͏ͪմੵ˕ࡗຌ எध   ɼࢃ஖ ༐୉   ɼӮీ ਺   ɼฤฑ ਜ਼ਕ   ‫౐ښ‬୉ָΦϋϩάʖཀྵ޽ָ‫ॶڂݜ‬ɼ ‫౐ښ‬୉ָ୉ָӅΦϋϩάʖՌָ‫ڂݜ‬Ռ
3

,QFHOO105 ͶΓΖ OLQHDUGLXELTXLWLQ ͹ LQVLWX ཱིରߑଆմੵ
˕Բ෨ ষ୉  ɼీ‫྆ ؝‬ഇ  ɼ‫ ీࢦכ‬Ҳ  ɼඔઔ ແ  ɼஶ‫ߌ ފ‬ղ  ɼஓ୫ రฎ  ɼґ౽ ཾ  ౨‫ཱི౐ښ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬Ռɼ ཀྵԿָ‫ॶڂݜ‬ਫ਼ໍ‫ؽ‬೵Ռָ‫ڂݜ‬ιϱνʖ


3<

Կָεϓφ͖ΔਬఈͤΖϖϨρέη‫ܙ‬੔ׄ߻˕༆ీ ိध  ɼ٤ీ ੜඔ  ɼ౽‫ ݬ‬࿪෋   ɼஓ޳ կಕ   ૓Ճ୉ָ୉ָӅཀྵ޽ָ‫ڂݜ‬Ռਫ਼ໍཀྵָ઒ߊɼ ૓Ճ୉ָ୉ָӅ޽ָ‫ڂݜ‬Ռਫ਼ໍ৚ๅ޽ָ઒ߊ

3

߶ѻ 105 ๑ͶΓΖφϧϱηγ΢Ϫοϱ͹ѻྙร੓͹մੵ˕ബ୫ চԟ  ɼࢃຌ ‫  ߵښ‬ɼ੼ࡖ Ҳ೯  ɼۜ઄ ‫  ್ݣ‬‫ܵ޽౐ښ‬થң୉ָ୉ָӅ‫ؽ‬೵෼࣯Կָ઒ߊɼ ͜͏ͺΞ͵ชԿָढ़‫ڢ‬ճ


3<

ηά‫;ٶ‬ι΢ϦΤ΢φηά՘ฆ༟པ *53 ΠϪϩΰϱ͹ཱིରߑଆմੵ
˕൩௫ ༓ࡌ  ɼṆ ༅߃  ɼ‫ٳ‬ธీ ദ೯  ɼ‫ۿ‬໨ ߃༡  ɼ՘Ԯ ҏඔ  ɼ٤ઔ Ҳิ  ɼ஦౤ ༓ཀྵࢮ  ɼ੶‫ ݬ‬ᰞഇ  ɼ૮ୖ ஒ߃  ๼քಕ୉ָ୉ָӅਫ਼ໍՌָӅɼ ๼քಕ୉ָ୉ָӅ઎୼ਫ਼ໍՌָ‫ڂݜ‬Ӆ

－ 32 －


3ϕϫφϱఽ಍੓Πϩάϱ࢐ΠϩΫϩ΢ϝξμʖϩ෵߻ର͹෾ࢢӣಊͳ‫ߑॶۃ‬ଆ˕ࡋߒ ࡌʓ՘  ɼ‫୕ ݬ܂‬໷  ɼ॑ీ ଻޼  ɼӏਁ ᠵ‫  ޝ‬ɼҬీ ๐ஒ  ɼਭ໼ ‫ݫ‬ദ   ۜୖ୉ָ୉ָӅࣙષՌָ‫ڂݜ‬Ռɼ ۜୖ୉ָψόϜτϨΠϩ‫ॶڂݜ‬


3<

. ݃߻‫؂ܗ‬য়ϤϑΫοϱ࠱͹෼੓մੵ˕‫ ీۯ‬எध  ɼਁຌ ୉ஒ  ɼ(ULN:DOLQGD ɼ੃ੋ ‫  ࣑ݢ‬‫౐ښ‬୉ָ୉ָӅ޽ָ‫ڂݜ‬Ռɼ ‫౐ښ‬୉ָ୉ָӅҫָ‫ڂݜ‬Ռɼ ‫౐ښ‬୉ָ୉ָӅ೸ָ‫ڂݜ‬Ռ
3

,QFHOO105 ͶΓΖ .HDS1UI ‫ܧ‬͹‫ڂݜ‬˕๝ీ լਫ਼  ɼஶ‫ߌ ފ‬ղ  ɼ຦߁ ࢦ৭  ɼౣ քᠵ  ɼஓ୫ రฎ  ɼྵ໨ ཾ࢛  ɼࢃຌ կ೯   ɼґ౽ ཾ  ౨‫ཱི౐ښ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬ՌԿָ઒ߊɼ ౨๼୉ָ୉ָӅҫָ‫ڂݜܧ‬Ռɼ ౨๼ϟυΡΩϩʀϟΪώϱέ‫ߑؽ‬3<+&9 ΰόϞ 51$ ͶଚࡑͤΖΫρεϱήϩʖϕߑଆ͹մੵ˕ཻग Ό͛Ί  ɼՑ߻ ߸ଢ  એཁ޽‫ۂ‬୉ָ
3‫ݽ‬ର 105 Ν༽͏ͪϐφ೶༟པ $Ў તң͹‫ڂݜ‬Ͷ͕͜Ζࢾྋ͹࠹నԿͳߑଆմੵ˕࣋‫  ڻ ݡ‬ɼ॑ޭ Մ‫  خ‬ɼনీ ༒  ɼ੶Ҭ Մ༬   ౨‫ۂ޽ښ‬୉ָਫ਼ໍཀྵ޽ָӅɼ ཀྵԿָ‫ॶڂݜ‬ਫ਼ໍ‫ؽ‬೵Ռָ‫ڂݜ‬ιϱνʖ઎୼ 105 ֋൅ʀԢ༽

οʖϞ

3

࣍କՆ೵͵߶෾ࢢࡒྋઅ‫ܯ‬Νࢨ޴ͪ͢ 105 ‫ى‬फ़ࢢபड़
˕๼ࢃ ᠵ໾  ɼԥࢃ ୉‫   م‬ɼ௸Ҭ ༡ཀྵ  ɼ٢ஏ ५    ԥශࢤཱི୉ָ୉ָӅਫ਼ໍҫՌָ‫ڂݜ‬Ռɼ ཀྵԿָ‫ݱࣁڧ؂ॶڂݜ‬Ռָ‫ڂݜ‬ιϱνʖ‫ڧ؂‬େः෾ੵ‫ڂݜ‬οʖϞɼ ໌‫ݻ‬Բ୉ָ୉ָӅਫ਼ໍ೸ָ‫ڂݜ‬Ռ
3

105 ͶΓΖถ࠱१‫཰ࣞ؂‬৏཈৫‫ڗ‬͹େःʀ೓࣯෾ੵ˕‫ ڰ؛‬Ѭඔ  ɼԥࢃ ୉‫  م‬ɼࡖీ ‫  ್ݜ‬ɼ࣋ࢃ ‫   ܝ‬ɼ٢ஏ ५    ԥශࢤཱི୉ָཀྵָ෨ਫ਼ໍҫՌָՌɼ ԥශࢤཱི୉ָ୉ָӅਫ਼ໍҫՌָ‫ڂݜ‬Ռɼ ཀྵԿָ‫؂ॶڂݜ‬‫ݱࣁڧ‬Ռָ‫ڂݜ‬ιϱνʖɼ ໌‫ݻ‬Բ୉ָ୉ָӅਫ਼ໍ೸ָ‫ڂݜ‬Ռ
3Πϝό࢐รҡͳѻྙઃಊΝ༽͏ͪνϱϏέ࣯͹ร੓஦ؔର͹҈ఈԿ˕๼ୖ ૓Ҳ࿢  ɼऑຌ ୕࿗  ɼࢃຌ ९໷  ɼঘड़ ྱ಺  ɼ๼‫  ྆ ݬ‬ཱིໍ‫ؙ‬୉ָ༂ָ෨ɼ ཱིໍ‫ؙ‬୉ָӅਫ਼ໍՌָ෨ɼ ཱིໍ‫ؙ‬୉ָӅ༂ָ෨

－ 33 －

3ঘ๖ରຜؑ௪஁പ࣯ 9$3% ‫ ;ٶ‬9$3%))$7PRWLI ෵߻ର͹ 105 ߑଆմੵ
˕‫ރ‬ઔ ߦ  ɼ‫ݻ‬൚ ‫  ࢢڭ‬ɼঘྜྷ ௜޼  ɼ౽‫ ݬ‬ෆಕ  ɼࣉ౤ ௗ࣏࿢   ԥශࠅཱི୉ָ୉ָӅཀྵ޽ָැɼ ୉ࡗ୉ָ஁പ࣯‫ॶڂݜ‬ɼ ཀྵԿָ‫ޭࣻ๎ॶڂݜ‬Ռָ‫ڂݜ‬ιϱν

ʖ

3<

'13105 ͶΓΖΨένυεϩεϨϩεϨΩΰϩන໚Ͷ͕͜ΖΠϩΫϩηϩϙαύέ࢐෾ࢢ‫ٷ‬஥ߑଆ͹մੵ
˕࡭‫ٳ ݬ‬෤  ɼྵ໨ ࠂ໎  ɼԮଞ །  ɼ੪໼ ‫ܛ‬ଢ  ɼྵ໨ ෈ཱ  ɼׁ ߄ఱ  ՘Ԩ‫ࣞה‬ճऀɼ ‫౐ښ‬୉ָԿָ‫ॶڂݜ‬
3

৙ࣕ੓ 105 Ν༽͏ཽͪࠞۗϜϩοχϟ΢ϱ஁പ࣯ )L[- ͹ཱིରߑଆմੵ
˕୉‫ٳ‬ฯ ཮Մ  ɼஓ୫ రฎ  ɼోᬔ ཥٍ  ɼඝ૖ ௜ध  ɼࢀౣ ਜ਼‫   و‬ɼஶ‫ߌ ފ‬ղ  ɼঘघ੶ ଻߃  ɼᖔҬ ਖඔ  ɼ৕ ઑ࢜  ɼґ౽ ཾ  ౨‫ཱི౐ښ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬ՌԿָ઒ߊɼ ฎ‫ཱིݟށ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬Ռɼ ౨‫ښ‬༂Ռ୉ָ༂

ָ෨

3<

࢔‫خ‬ಝҡద͵೦ྙָʀଐౕ࿨մੵ͗໎Δ͖ͶͤΖ VSHFWULQ6+ χϟ΢ϱ͹ϓΧʖϩυΡϱή‫ؽ‬ߑ˕ྜྷ ੔Ҳ࿢  ɼ౽࿚ ୉ื  ɼਈీ ୉ื  ۟य୉ָਫ਼ର๹‫ޜ‬ҫָ‫ॶڂݜ‬ɼ ੫Ԯ‫ཱིݟ‬୉ָ༂ৱਫ਼ໍՌָ૱߻ָැ3॑‫ݫ‬ો͹ 105 ԿָεϓφೳౕรԿͶ‫ͤؖ‬Ζ ')7 ‫ ࢋܯ‬૮ଲ࿨ްՎͶ‫؏͚Ͱخ‬଎‫Ͳ಼֫ࢢݬ‬͹ుࢢηϒϱືౕ͹‫ݳ‬Η˕௉૖ ༟ޭ  ɼ‫ ݬ܄‬୉ղ  ɼ஦ઔ ௜࠺  ు‫ـ‬௪৶୉ָ୉ָӅ৚ๅཀྵ޽ָ‫ڂݜ‬Ռ


3<

ϝϣʖΨϒΨ΢χण༲ର͹ΠϫητϨρέϠζϣϪʖνʖͶΓΖ‫׈‬੓Կ‫ߑؽ‬͹մ໎˕ۜࢢ ।   ɼࠕҬ ॥ื  ɼછඎ ৶ԟ   ɼ߀ෳ ༡  ɼ৏ీ ୐‫  ݡ‬ɼ౤ీ Ҳ෋  ཀྵԿָ‫ॶڂݜ‬ਫ਼ໍ‫ؽ‬೵Ռָ‫ڂݜ‬ιϱνʖɼ ౨‫ښ‬୉ָ୉ָӅ༂ָ‫ڂݜܧ‬Ռ3Ϝϩοχϟ΢ϱ஁പ࣯ *5% ͳ 626350 ྘Ү͹૮‫༽ࡠޕ‬մੵ˕‫ؙ‬໼ ‫ܣ‬ଢ  ɼ੃ᖔ ͺΖ͖  ɼ҈౽ ߡ࢛  ɼీ୼ ਇ࠾ࢢ  ɼඔઔ ແ  ɼஶ‫ߌ ފ‬ղ  ɼߗൻ૵ ਜ਼߅  ɼࢀౣ ਜ਼‫   و‬ɼੁీ ༙࣑  ɼஓ୫ రฎ  ɼґ౽ ཾ  ౨‫ཱི౐ښ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬Ռɼ ཀྵԿָ‫ॶڂݜ‬ਫ਼ໍ‫ؽ‬೵Ռָ‫ڂݜ‬ιϱνʖɼ ཀྵԿָ‫ੁॶڂݜ‬ీཀྵ࿨෾ࢢՌָ‫࣪ڂݜ‬ɼ ౨‫ښ‬༂Ռ୉ָ༂ָ෨
－ 34 －

3<

৙ࣕ੓ 105 Ν༽͏ͪϜϩοχϟ΢ϱ஁പ࣯ *5% ͹ཱིରߑଆմੵ
˕҈౽ ߡ࢛  ɼ੃ᖔ ͺΖ͖  ɼ‫ؙ‬໼ ‫ܕ‬ଢ  ɼీ୼ ਇ࠾ࢢ  ɼඔઔ ແ  ɼ‫ٸ‬໼೘ ༺ฑ  ɼઔ୼ ༳ฑ  ɼ+LVKDP'RNDLQLVK ɼ:HLWRQJ5HQ ɼ୉ड़ ਇԟ  ɼ಼࣋ ห  ɼஶ‫ߌ ފ‬ղ  ɼࢀౣ ਜ਼‫  و‬ɼߗൻ૵ ਜ਼߅  ɼੁీ ༙࣑  ɼஓ୫ రฎ  ɼґ౽ ཾ  ɼ౨‫ཱི౐ښ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬Ռɼ ཀྵԿָ‫ॶڂݜ‬ਫ਼ໍ‫ؽ‬೵Ռָ‫ڂݜ‬ιϱνʖɼ ୉ࡗ୉ָ஁പ࣯

‫ॶڂݜ‬ɼ ཛ೸ָԄ୉ָৱͳ݊߃ָྪɼ ཀྵԿָ‫ీੁॶڂݜ‬ཀྵ࿨෾ࢢԿָ‫࣪ڂݜ‬ɼ ଢཇೖ࢐ 6, ΢όϗʖεϥϱιϱνʖɼ ౨‫ښ‬༂Ռ୉ָ༂ָ෨3‫΃ྪڗ‬͹Ϝ΢έϫϕϧηορέઃ㕔Ͷ͕͜ΖେःϕϫϓΟ΢ϩ҈ఈ੓඲Ճ
˕নӮ Ҳଢ   ɼൂ໨ ୣ‫  ن‬ɼࡖీ ‫  ್ݜ‬ɼ٢ஏ ५    ԥශࢤཱི୉ָ୉ָӅਫ਼ໍҫՌָ‫ڂݜ‬Ռਫ਼ໍҫՌָ઒ߊɼ ཀྵԿָ‫ݱࣁڧ؂ॶڂݜ‬Ռָ‫ڂݜ‬ιϱνʖ‫ڧ؂‬େः෾ੵ‫ڂݜ‬οʖϞɼ ໌‫ݻ‬Բ୉ָ୉ָӅਫ਼ໍ೸ָ‫ڂݜ‬Ռ3<%XOOHW'13 Ν༽͏ͪϒϩϑϱ࢐͹߮ોൕԢࣰ‫ݩ‬˕๮݆ ༐‫  ن‬ɼ਄ᖔ ६  ɼࠞཔ ੥   ɼ๼ઔ ঋߔ   ɼߵઔ ߌಛ   ୉ࡖ୉ָ୉ָӅ‫ڂݜָ޽ેخ‬Ռɼ ୉ࡗ୉ָ઎಍దָࡏ‫ࢢྖߑؽڂݜ‬৚ๅʀྖࢢਫ਼ໍ‫ڂݜ‬ιϱνʖɼ ྖࢢՌָٗढ़‫֋ڂݜ‬൅‫ߑؽ‬
3ϘϫϔηΩ΢φ‫࢐ܗ‬஢Կ෼͹ 1 ‫ݽ‬ର 105 ͹࠸‫ݗ‬౾˕໼ీ ଻౉  ɼ੶Ҭ ࡫ࢢ  ɼ৿໨ ૳ଢ  ɼೖ෨ ༦ଢ  ɼṶᔻ ༓࣑  ɼ஝ࠌ ੜ೭ཀྵ  ‫౐ښ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬Ռɼ ๼քಕ୉ָ୉ָӅ޽ָ‫ڂݜ‬Ռ


3



& ͕Γ; 1 ඬࣟ ΠϝόϪϔϨϱ࢐͹߻੔ͳ 105 մੵ˕੪ࢃ ༺࢛  ɼ൩௫ ༐ղ  ɼӮߒ ่߀  ɼ߁ੋ ိ  ɼࢀౣ ਜ਼‫  و‬౨‫ښ‬༂Ռ୉ָ༂ָ෨ɼ ๝‫ٗڰ‬ढ़Ռָ୉ָ୉ָӅԢ༽Կָਫ਼ໍ޽ָ‫ܧ‬
3

0' ‫ࢋܯ‬ɼ਄૜ָसΝ‫ͪ͢༽׈‬νϱϏέ࣯෵߻ରմੵ
˕ঘྜྷ ௜޼  ɼঘব ߸  ɼ༙ీ ‫ڭ‬ฑ  ɼஓ৏ ‫  ٳي‬ɼࢃ࡜ य़෋  ཀྵ‫ݜ‬ਫ਼ໍ‫ؽ‬೵Ռָ‫ڂݜ‬ιϱνʖɼ ԥශࢤཱི୉ਫ਼ໍҫՌָ‫ڂݜ‬Ռ


3<

*03313 ݃߻‫ ܗ‬.5DV*9 ͳ 5JO5%' ͹૮‫༽ࡠޕ‬մੵ˕෍ֿ ௜೯  ɼ‫ ీٸ‬༡‫  ي‬ɼّҬ ॥  ɼ੃ᖔ ͺΖ͖  ɼඔઔ ແ  ɼஶ‫ߌ ފ‬ղ  ɼీ஧ Յେࢢ  ɼґ౽ ཾ  ɼஓ୫ రฎ  ౨‫ཱི౐ښ‬୉ָ୉ָӅཀྵָ‫ڂݜ‬Ռɼ Ϫηνʖ୉ָ෾ࢢࡋ๖ਫ਼෼ָՌɼ ཀྵԿָ‫ॶڂݜ‬ਫ਼ໍ‫ؽ‬೵Ռָιϱνʖ


－ 35 －

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߶Ի௔ఽ಍ώϩέࣕ੶න໚‫ޱ‬ഓࣕ৖Ν༽͏ͪ֨ࢆ 105 ଎ఈૹ஖͹֋൅ ϨοΤϞ΢Ψϱుஓ֋൅Ͷన߻ͤΖ଎ఈૹ஖Ν໪ࢨ͢ͱ
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ਸ਼1঩৯
11া8঩‫كౌق‬঩মୁ७ॵ३ঙথ

Day 1
Tuesday, 8th Nov.
Japanese Sessions

L1-1

1 H–13 C 二重共鳴 NMR のための小型電気–機械–光変換プローブ

 冨永雄介，武田和行
京都大学大学院 理学研究科

Electro-mechano-optical NMR probe for 1 H-13 C double resonanceYusuke Tominaga, Kazuyuki Takeda
Graduate School of Science, Kyoto University
We report development of a compact EMO NMR probe compatible with superconducting magnets
used in NMR for chemical analysis, demonstrating 1 H–13 C refocused INEPT followed by EMO 13 C
NMR detection in liquid benzene.

1

Introduction

NMR は物理・化学・生物学などの多岐にわたる分野で構造やダイナミクスの解析に用いられ，強力な分析手法として発展してきた．しかし，NMR は原理的に感度が低い．NMR の発展の歴史
は感度向上の手法開発の歴史でもあり，現在もなお，NMR の感度向上は重要な課題である．
我々は，NMR の感度向上をめざして，NMR 信号を光変換する装置の開発を行ってきた．信号の光変換は図 1a に示すような系で行い，ここでは金属が蒸着された高い Q 値を持つ窒化ケイ素薄膜が二つの役割を担う．第一に，蒸着金属は NMR 信号受信回路のキャパシタ電極として組み込
まれ，NMR 信号は薄膜の振動に変換される．第二に，蒸着金属はミラーとして用いられ，光の干渉により薄膜の振動を読み取ることができる．光に変換するこの方法（Electro-Mechano-Optical
で EMO と呼ぶ）では，室温下でも，加わるノイズを限りなく小さくすることができ，NMR の感度を向上することができると考えられている [1, 2, 3]．
通常，光学系は地面振動などの影響を抑えるために，大掛かりな光学定盤の上に構築され，精密なアライメイトを要する．しかし，化学分析用の NMR で用いられる均一度の高い超伝導磁場中で EMO NMR 測定を行うためには，限られたスペースの中に光変換系を組み込み，光学装置の精
確なアライメントを行い光検出する必要がある．その実現のために，本研究では図 1b のような超伝導磁場内に挿入できる小型な EMO NMR プローブを作成した．そして，リフォーカス INEPT法を適用し，ベンゼンの 13 C NMR 信号を EMO により光変換して取得することに成功した [4]．

2

Design & Fabrication

5 mm× 5 mm の大きさの Si 枠に張られた厚さ 200 nm，大きさ 1 mm× 1 mm の窒化ケイ素薄膜上に厚さ 40 nm のアルミニウム層を蒸着した．電極がプリントされた大きさ 5 mm× 5 mm のプリント基板上には，重ねたときに伱間を作るためにアルミニウムを 500 nm 蒸着し，Si 枠上に．空気による薄膜の振このプリント基板を重ね合わせることで薄膜キャパシタを作製した（図 2a）動の減衰を防ぐために，薄膜は真空下に設置した．
自作の真空チャンバーの設計は図 2b のようになっている．直径 60 mm であり，超伝導磁石のボアに収まるようにしている．真空チャンバーの蓋を閉じるだけで，薄膜キャパシタとの電気的な接触が取れて外部からアクセスできるようになっており，配線は可能な限り短くなっている．
オプトメカニクス，光変換，INEPT とみながゆうすけ，たけだかずゆき－ 42 －

(a)(b)
LC circuit

Coilattachable

Membrane module
Membraneoscillator
Lens & Collimator

60 mm
Optical detection

Fig. 1 (a) A schematic diagram of EMO NMR. NMR signals are transduced to the membrane
oscillation through the LC circuit. The resulting membrane oscillation is in turn read out opticallywith the optical interference. (b) A snapshot of the probe for EMO NMR operational inside thebore of a superconducting magnet.

薄膜上の蒸着金属は光共振器のエンドミラーとしても用いる．真空チャンバー内に光共振器の．
フロントミラーも設置して，共振器長は 2.54 mm に設計してモードマッチングを取った（図 2c）
共振器はなるべく短く，またモノリシックな構造にすることで，安定な光学検出を実現している．
ミラーを設置したプレートと真空チャンバー間をシールしている O-リングは，非磁性のばねとしてミラーのアライメントにも利用することができる．
この真空チャンバー内に構成した EMO システムと，NMR 信号の励起・受信用の二重共鳴回路，レーザービーム整形用の光学系とを連ねて NMR 信号を光検出できるようにしたプローブが
図 1b に示したものである．

3

Results

4.7 T の磁場における 1 H および 13 C のラーモア周波数に対して，NMR 励起・検出用の LC 回路の同調をとり，インピーダンス整合もとった．リフォーカス INEPT で信号増強されたベンゼンの 13 C の NMR 信号を 1 H デカップリング下で取得するためのパルスシーケンスは図 3a の通りである．EMO NMR の実施においては，電気-機械結合を誘起するために交流電圧を薄膜キャパシタ
上にかけてドライブする必要がある．パルスを照射している間は，パルスが薄膜の振動に変換されないようにドライブの周波数をずらしておき，信号の取得の間だけ信号が変換されるような交流周波数にした．
図 3b,c に示したものは EMO NMR により取得した，リフォーカス INEPT により増強された
13 C-labeled ベンゼンの NMR 信号と，そのフーリエ変換スペクトルである．比較のために，同様に励起し受信した信号を光変換せずに，従来の NMR で行われるように電気的に増幅して取得したのが図 3d,e である．EMO NMR と通常の電気的な NMR で，得られた信号はほとんど一致していたが，差異も検出の帯域幅の違いによって説明できる．EMO による検出では，薄膜の帯域幅（約 100 Hz）によって制限されるため，帯域の外ではノイズが非常に小さいが，帯域内では薄膜の熱雑音が観測される．薄膜の熱雑音は，電気–機械結合を大きくすることにより，原理的には小さ－ 43 －

(a)(b)

Al pad(c)hermetic port

1 mm

2.54

contact probe

ROC =10

ip
&
pile

Al mirror/electrode197

membrane
capacitor

pillarvacuum port
cavity mirror

holewindow

4.05
collimated laser(unit: mm)

60 mm

electrodef = 200

Fig. 2 (a) A 5 mm×5 mm Si frame supporting a 1 mm×1 mm Si3 N4 membrane, on which analuminum layer for the capacitor electrode and the optical mirror was made by vacuum deposition.
A printed circuit board serving for the counter electrode was piled on the Si frame. (b) Cross
sectional view of a cylindrical vacuum chamber containing the membrane capacitor. (c) Designof the optical cavity for a collimeted laser beam with an incident beam diameter of 4.05 mm. A
concave mirror with a radius of curvature (ROC) of 10 mm and a lens with a focal length (f) of
200 mm were combined to form the cavity. (Reproduced from Ref. [4] with permission from theRoyal Society of Chemistry.)


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

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



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 

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*

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#

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Fig. 3 (a) A pulse sequence for refocused INEPT with 1 H decoupling. (b, c) A refocused INEPT
enhanced 13 C NMR signal and Fourier-transformed spectrum of 13 C-labeled benzene obtained by
the EMO scheme. (d, e) The same signal and spectrum obtained by the conventional electricaldetection. (Reproduced from Ref. [4] with permission from the Royal Society of Chemistry.)－ 44 －

(a)

(b)

0

dB

-20
-40
-60
386

388

390

392

50.34350.34450.34550.346MHz

kHz

Fig. 4 (a) A power spectrum of an optical signal around the frequency 388.18 kHz of membranecharacteristic oscillation, on which the signal at 50.34455 MHz was transduced. (b) A power
spectrum of an electrical signal obtained by amplifying the same signal. (Reproduced from Ref. [4]with permission from the Royal Society of Chemistry.)

くすることができる．
EMO NMR と電気的な NMR の感度を直接比較し性能を評価するために，強度のわかっている
電気信号をシンセサイザで合成し，連続的に LC 回路内に発生させた．−121.6 dBm の信号を光変換して観測されたパワースペクトルは図 4a であり，同じ信号を電気的に増幅して観測されたパワースペクトルは図 4b であった．EMO 検出の場合，薄膜の熱振動由来のローレンツ形のスペク
トルにより，雑音強度が大きくなっているが，その帯域の外では電気的な検出の雑音よりも小さくなっていることがわかる．したがって，薄膜の熱雑音の寄与を小さくすることができれば，従来の電気的な増幅による検出法に EMO NMR は感度の点で優位になる可能性があることがわかる．
以上のように，広く使用される手法である INEPT と組み合わせた EMO NMR を，超伝導磁石内で行うことに成功したことにより，これまで主に物理学的な興味対象であった EMO NMR を化
学分析にも応用する道を開いたといえる．EMO NMR の感度はまだ薄膜の熱雑音に制限されてはいるものの，従来の電気的な方法とも比較可能な領域にあり，今後さらに電気–機械結合を大きくしたり，レーザー冷却の手法と組み合わせたりすることにより，高感度な検出方法としての利用が期待できる．

References[1] Kazuyuki Takeda, Kentaro Nagasaka, Atsushi Noguchi, Rekishu Yamazaki, Yasunobu Nakamura,
Eiji Iwase, Jacob M Taylor, and Koji Usami. Electro-mechano-optical detection of nuclear magnetic resonance. Optica, 5(2):152–158, 2018.
[2] Yusuke Tominaga, Kentaro Nagasaka, Koji Usami, and Kazuyuki Takeda. Studies on NMRsignal up-conversion from radio-frequency to optical regimes using a lightweight nanomembranetransducer. Journal of Magnetic Resonance, 298:6–15, 2019.
[3] Yusuke Tominaga, Atsushi Mikami, Akiya Iwamura, Koji Usami, and Kazuyuki Takeda. Heatingfree, room-temperature operation of a radiofrequency-to-light signal transducer with a membrane
oscillator and a built-in metasurface mirror. Applied Physics Express, 15(1):012003, 2021.
[4] Yusuke Tominaga and Kazuyuki Takeda. An electro-mechano-optical NMR probe for 1 H–13 C
double resonance in a superconducting magnet. Analyst, 147(9):1847–1852, 2022.

－ 45 －

L1-2

㧗 ㉸ఏᑟࣂࣝࢡ☢▼⾲㠃໙㓄☢ሙࢆ⏝࠸ࡓᣑᩓNMR ᐃ⿦⨨ࡢ㛤Ⓨ‫ۑ‬㧗ᶫ㞞ே㸪⳥ụ⩧㸪ᆏ஭┤㐨㸪ᮧୖ㞞ே㸪ᶓᒣ࿴ဢ㸪7ULWUDNDUQ7HFKLW㸪ᒸᮧဴ⮳㸪ᒸᚭ㞝㸪௰ᮧ㧗ᚿ1⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮2Ⱚᾆᕤᴗ኱Ꮫ኱Ꮫ㝔࣭⌮ᕤᏛ◊✲⛉3㊊฼኱Ꮫ࣭ᕤᏛ㒊4ᮾிᕤᴗ኱Ꮫ࣭ᕤᏛ㝔࣭ᶵᲔ⣔5⌮໬Ꮫ◊✲ᡤ࣭⎔ቃ㈨※⛉Ꮫ◊✲ࢭࣥࢱ࣮Development of a diffusion NMR measurement system using the surface gradient fieldof a high-temperature superconducting bulk magnet‫ۑ‬Masato Takahashi1,2, Sho Kikuchi2, Naomichi Sakai2, Masato Murakami2, Kazuya Yokoyama3, Techit
Tritrakarn4, Tetsuji Okamura4, Tetsuo Oka1,2, Takashi Nakamura5,2
1RIKEN Center for Biosystems Dynamics Research
2Graduate School of Engineering and Science, Shibaura Institute of Technology
3Faculty of Engineering, Ashikaga University
4Department of Mechanical Engineering, Tokyo Institute of Technology
5RIKEN Center for Sustainable Resource Science

Diffusion NMR on the surface of a High-Temperature Superconducting (HTS) bulk magnet has been
demonstrated. HTS bulk magnets can generate a strong and stable magnetic field despite their compact
body size. The strong static field gradient on the surface can be effectively used for the measurement of
low-diffusion coefficients and high spatial resolution instead of no chemical shift information. The highspatial resolution in the direction of the gradient field is realized since the excitation bandwidth is muchsmaller than the NMR signal bandwidth broadened by the strong static field gradient in the sample.
Diffusion NMR with a strong static field gradient has different characteristics compared to commonly used
Pulse Field Gradient (PFG) diffusion NMR. These characteristics are suitable for the analysis of the ion
mobility in lithium-ion batteries around electrodes.
ᡃࠎࡣ㧗 ㉸ఏᑟࣂࣝࢡ☢▼ࢆ⏝࠸ࡓᣑᩓNMR ᐃ⿦⨨ࢆ㛤Ⓨࡋ࡚࠸ࡿ1ࠋ㧗☢▼ࡣࠊ㉸ఏᑟయࡢሢ࡛࠶ࡾᴟప

㉸ఏᑟࣂࣝࢡ

(40 K௨ୗ⛬ᗘ)࡟෭༷ࡋ☢ሙࢆぬ࠼ࡉࡏࡿࡇ࡜࡛ᙉຊ࡞☢ሙ

ࢆⓎ⏕ࡉࡏࡿࡇ࡜ࡀ࡛ࡁࡿࠋ┤ᚄ60 mm⛬ᗘ࡜㠀ᖖ࡟ࢥࣥࣃࢡࢺ࡛࠶ࡾࠊࡲࡓࡇࢀࡢ෭༷ࡣ஺ὶ
100 Vࡢ㟁※ࢆ౑ࡗࡓᐙᗞ⏝࢚࢔ࢥࣥ⛬ᗘࡢᾘ㈝㟁ຊ࡛࠶ࡿᴟప ᑠᆺ෭෾ᶵ࡛㈥࠼ࡿࡓࡵ⿦⨨඲యࡀ㠀ᖖ࡟ࢥࣥࣃࢡࢺ࡜࡞ࡿࠋࡇࢀࡲ࡛࡟௰ᮧࡽࡀ✚ᒙࡋࡓࣜࣥࢢ≧ࡢ㧗㉸ఏᑟࣂࣝࢡ☢▼ࢆ⏝࠸࡚ࠊඛ㗦࡞⁐ᾮNMRࢫ࣌ࢡࢺࣝࢆྲྀᚓࡍࡿࡇ࡜࡟ᡂຌࡋ࡚࠸ࡿ2ࠋࡇࡢ㧗 ㉸ఏᑟࣂࣝࢡ☢▼ࡢ฼Ⅼࢆࡼࡾά࠿ࡋࡓ⿦⨨ࢆ㛤Ⓨࡍࡿࡓࡵ࡟ࠊᣑᩓNMR࡟ὀ┠ࡋࡓࠋࢥࣥࣃࢡࢺ࡞ࢧ࢖ࢬ࡛ᙉຊ࡞☢ሙࡀⓎ⏕ࡋ࡚࠸ࡿ࡜࠸࠺ࡇ࡜ࡣࠊࡑࡢ⾲㠃࡟ࡣᙉຊ࡞໙㓄☢
㧗㉸ఏᑟࣂࣝࢡ☢▼㸪ᣑᩓNMR㸪∦ഃNMR‫࡜ࡉࡲࡋࡣ࠿ࡓۑ‬㸪ࡁࡃࡕࡋࡻ࠺㸪ࡉ࠿࠸࡞࠾ࡳࡕ㸪ࡴࡽ࠿ࡳࡲࡉ࡜㸪ࡼࡇࡸࡲ࠿ࡎࡸ㸪࡜ࡾ࡜ࡽ࠿࣮ࢇ࡚ࡋࡗ࡜㸪࠾࠿ࡴࡽ࡚ࡘࡌ㸪࠾࠿࡚ࡘ࠾㸪࡞࠿ࡴࡽࡓ࠿ࡋ

－ 46 －

ሙࡀⓎ⏕ࡋ࡚࠸ࡿࡇ࡜ࢆព࿡ࡋ࡚࠸ࡿࠋ໙㓄☢ሙࢆ⏝࠸ࡿ ᐃᡭἲ࡜ࡋ࡚ࡣᣑᩓNMRࡀ࠶ࡿࠋ⌧ᅾࡢᣑᩓNMRࡣPulse Field Gradient(PFG)ࢆ⏝࠸࡚ࠊᚲせ࡞ࢱ࢖࣑ࣥࢢࡔࡅ▐㛫ⓗ࡟໙㓄☢ሙࢆ
Ⓨ⏕ࡉࡏ࡚࠸ࡿ3ࡀࠊPFGࡀⓎ᫂ࡉࢀࡿ๓ࡣ㟼☢ሙ໙㓄࡛ᣑᩓNMRࡢ ᐃࡀ⾜ࢃࢀ࡚ࡁࡓࠋPFGࢆ⏝࠸ࡿࡇ࡜࡟ࡼࡗ࡚ࠊNMRಙྕࢆྲྀᚓࡍࡿࢱ࢖࣑ࣥ
ࢢ࡛ࡣᆒ୍☢ሙࢆ฼⏝ࡍࡿࡇ࡜ࡀ࡛ࡁࠊࡇࢀ࡟ࡼ
ࡾ໬Ꮫࢩࣇࢺ᝟ሗࡀྠ᫬࡟ᚓࡽࢀࡿ࡞࡝ከ኱࡞฼
Ⅼࡀ࠶ࡿࠋࡋ࠿ࡋࠊ⌧ᅾ࡛ࡣᛀࢀཤࡽࢀ࡚ࡋࡲࡗ
ࡓ㟼☢ሙ໙㓄࡟ࡼࡿᣑᩓNMR ᐃ࡟ࡶ࠸ࡃࡘ࠿฼
Ⅼࡀ࠶ࡿࠋࡲࡎࠊ㟼☢ሙ໙㓄࡛ࡣPFG࡛ࡣᐇ⌧࡛

Fig. 1. High-Temperature Superconducting(HTS) bulk material used in this study.

ࡁ࡞࠸ᙉຊ࡞☢ሙ໙㓄ࡀ㐩ᡂྍ⬟࡛࠶ࡿࠋᙉຊ࡞
PFGࡣࠊᙉຊ࡞PFG㟁※࡜Ỉ෭㟁☢▼࡟ࡼࡾຊᢏ࡛
ᐇ⌧ࡋ࡚࠾ࡾࠊ⌧ᅾ࠾࠾ࡼࡑ30 T/mࡀ᭱኱್࡛࠶
ࡿࠋ୍᪉ࠊᮏ◊✲࡛ࡣࠊ᭱ึࡢ୍Ṍ࡜ࡋ࡚ᙅࡃ╔☢ࡋࡓ㧗 ㉸ఏᑟࣂࣝࢡ☢▼࡛ࡍ࡛࡟60 T/m⛬ᗘࢆᐇ⌧ࡋ࡚࠸ࡿࠋ
ḟ࡟ࠊヨᩱࡶࡋࡃࡣヨᩱࡢ୍㒊ࡀ㧗࠸ᑟ㟁ᛶࢆᣢࡘሙྜࡣࠊPFG࡟ࡼࡿᛴ⃭࡞☢ሙኚື࡟ࡼࡾࡑ
ࡢᑟ㟁ᛶ㒊ศ࡟ 㟁ὶࡀⓎ⏕ࡋ໙㓄☢ሙศᕸࡀᔂ
ࢀ࡚ࡋࡲ࠺Ⅼ࡛࠶ࡿࠋ㟼☢ሙ໙㓄ࡢሙྜࡣ☢ሙࡀᖖ࡟୍ᐃ࡛࠶ࡿࡓࡵࡇࡢࡼ࠺࡞⌧㇟ࡣⓎ⏕ࡋ࡞࠸ࠋࡶ࠺ࡦ࡜ࡘࡣࠊ㟼☢ሙ໙㓄࡟ࡼࡿNMRࢫ࣌ࢡࢺࣝࡢᗈᖜ໬ࡀࠊບ㉳ᖜࡼࡾࡶࡣࡿ࠿࡟኱ࡁ࠸ࡓ
ࡵ⤖ᯝⓗ࡟㟼☢ሙ໙㓄᪉ྥ࡟㧗࠸✵㛫ศゎ⬟ࡀᚓࡽࢀࡿࡇ࡜࡛࠶ࡿࠋࡇࡢⅬࡣᚋ࡯࡝ヲ㏙ࡍࡿࠋ
NMRࡣ㏻ᖖ㧗࠸☢ሙᆒ୍ᗘ୰࡛ ᐃࡀ⾜ࢃࢀࡿFig. 2. Home-build NMR spectrometer using
Software Defined Radio (SDR), NI USRP2920.

ࡇ࡜ࡀᮃࡲࡋ࠸ࡓࡵࠊ☢▼࡟ᅖࡲࢀࡓ✵㛫㸦☢▼࣎࢔㸧ࡢ┿ࢇ୰࡛ ᐃࢆ⾜࠺ࡇ࡜ࡀᬑ㏻࡛࠶
ࡿࠋ㏻ᖖࡢNMR⿦⨨࡛ࡣ㉸ఏᑟ☢▼ࡢ࣎࢔࡟ࣉ࣮ࣟࣈࢆᤄධࡋ࡚ ᐃࢆ⾜࠺ࠋࡍ࡞ࢃࡕࠊ ᐃヨᩱࡢࢧ࢖ࢬࡣࠊ☢▼࣎࢔ࡼࡾࡶ㸦ࡶࡗ࡜ゝ࠼ࡤࣉ࣮ࣟࣈ┤ᚄࡼࡾࡶ㸧ᑠࡉ࠸ࡇ࡜ࡀᚲせ࡜࡞ࡿࠋ୍᪉࡛ヨᩱࢧ࢖ࢬ࣭ᙧ≧࡟ไ㝈࡞ࡃNMR ᐃࢆࡍࡿࡓࡵ࡟BlümichࡽࡣࠊỌஂ☢▼ࡢ⾲㠃࡛
NMR ᐃ࡟ᣮᡓࡍࡿඛ㥑ⓗ࡞ヨࡳࢆ⾜ࡗ࡚࠾ࡾ4ᣑᩓNMR ᐃࡶ⾜ࡗ࡚࠸ࡿ5ࠋᙼࡽࡣ⮬ศࡓࡕࡢ⿦⨨ࢆNMR-MOUSE࡜࿧ࢇ࡛࠸ࡿࠋ
ࡇࢀࡽࢆ㋃ࡲ࠼ࠊᮏ◊✲࡛ࡣ㧗 ㉸ఏᑟࣂࣝࢡ☢▼ࡀⓎ⏕ࡍࡿᙉຊ࠿ࡘᏳᐃ࡞㟼☢ሙ໙㓄ࢆ฼⏝ࡋࡓᣑᩓNMR ᐃ⿦⨨ࡢ㛤Ⓨࢆ⾜ࡗࡓࠋ㧗㉸ఏᑟࣂࣝࢡ☢▼࡟ࡣࠊ᪥ᮏ〇㕲ᰴᘧ఍♫〇ࡢFig. 1࡟♧ࡍ┤ᚄ65 mmࠊཌࡉ15 mmࡢࡶࡢࢆ⏝࠸ࡓࠋࡇࢀࢆ┤ᚄ87 mmࡢ┿✵ᐜჾ࡟཰⣡ࡋᑠᆺࡢGM෭෾ᶵ࡛30 Kࡲ࡛෭༷ࡋࡓࠋ╔☢ࢥ࢖ࣝࢆ⏝࠸ࡓࣃࣝࢫ╔☢ἲ,6,7࡟ࡼࡾࠊ30ศࡈ࡜࡟6ᅇࡢ╔☢ࢆ⾜ࡗࡓࠋ╔☢ࢥ࢖ࣝࡢ᭱኱㟁ᅽࡣ
690 Vࠊ᭱኱㟁ὶࡣ313 A࡛࠶ࡿࠋࡇࢀ࡟ࡼࡾ┿✵ᐜჾ⾲㠃࡛᭱኱1.83 Tࡢ☢ሙࢆᚓࡓࠋ
NMR ᐃ࡟ࡣࠊFig. 2࡟♧ࡍ⮬సࡢศගィࢆ⏝࠸ࡓࠋࢼࢩࣙࢼࣝ࢖ࣥࢫࢶ࣓ࣝࣥࢶ♫〇ࡢ
USRP-2920ࡣSoftware-Defined Radio(SDR)࡜࿧ࡤࢀࡿࠊࡇࢀࡲ࡛ࣁ࣮ࢻ࢙࢘࢔࡛ᐇ⌧ࡉࢀ࡚ࡁࡓ
ᶵ⬟ࢆࢯࣇࢺ࢙࢘࢔࡛ᐇ⌧ࡍࡿ⿦⨨࡛࠶ࡿࠋࡇࡢ⿦⨨ࢆไᚚࡍࡿࢯࣇࢺ࢙࢘࢔ࢆࢼࢩࣙࢼࣝ࢖ࣥ

－ 47 －

ࢫࢶ࣓ࣝࣥࢶ♫〇ࡢLabVIEW࡜NI-USRPࢆ⏝࠸࡚⮬సࡋNMRศගィ࡜ࡋ࡚฼⏝ࡋࡓࠋᣑᩓNMRࢆ ᐃࡍࡿࣉ࣮ࣟࣈ࡜ࡋ࡚ࠊ
እᚄ1.4 mmࠊෆᚄ1 mmࡢPTFEࢳ࣮ࣗࣈ࡟
㖡⥺ࢆᕳࡁ௜ࡅࡿࡇ࡜࡛Fig. 3࡟♧ࡍࣉ࣮ࣟࣈࢆ〇సࡋࡓࠋ ᐃヨᩱ✵㛫ࡣ┤ᚄ1mmࠊ㛗ࡉ2 mm࡛࠶ࡿࠋບ㉳⏝࢔ࣥࣉ࡟
ࡣ1 Wࡢࡶࡢࢆ⏝࠸ࠊ180ᗘࣃࣝࢫ㛗ࡣ8Ps࡛࠶ࡿࠋ ᐃ࡟ࡣࢫࣆ࢚ࣥࢥ࣮Carr-

Fig. 3. Schematic view of the setup for diffusion NMR

Purcell-Meiboom-Gill(CPMG)ࢆ⏝࠸ࡓࠋ㟼using a single-sided HTS bulk magnet. The HTS bulk☢ሙࡀ୙ᆒ୍࡛࠶ࡿࡓࡵࠊNMRࢫ࣌ࢡࢺ

magnet generated a strong magnetic field from theࣝࡣ㉸ᗈᖜࠊᚤᙅ࡜࡞ࡿࠋࡑࢀࢆ⿵࠺ࡓ

round surface.

ࡵ࡟CPMGࢆ100ᅇ⧞ࡾ㏉ࡋ࡚ࠊ࢚ࢥ࣮ಙ
ྕࢆ✚⟬ࡋࡓࠋ
㟼☢ሙ໙㓄࡟࠾ࡅࡿᣑᩓNMRࡢಙྕᙉᗘẚࡣḟࡢᘧ࡛࠶ࡽࢃࡉࢀࡿࠋ
Sሺ‫ݐ‬ா ሻ
1
‫ݐ‬ா
ln ቆ
ቇ = - ߛ ଶ ‫ܩ‬଴ଶ ‫ݐ‬ாଷ D െ  ሺͳሻ
SሺͲሻ
ܶଶ
12
S(t)ࡣ࢚ࢥ࣮ࡢᚅࡕ᫬㛫t࡟࠾ࡅࡿNMRಙྕᙉᗘࠊȚࡣ᰾☢Ẽᅇ㌿ẚࠊG0ࡣ㟼☢ሙ໙㓄ࠊDࡣ⮬ᕫᣑᩓಀᩘࠊT2ࡣᶓ⦆࿴᫬㛫ࢆ♧ࡍࠋ࢚ࢥ࣮ࡢᚅࡕ᫬㛫tEࢆቑࡸࡍ࡟ࡘࢀ࡚ಙྕᙉᗘࡀᑠࡉࡃ࡞ࡿࠋ᰾
☢Ẽᅇ㌿ẚȚࠊ㟼☢ሙ໙㓄G0ࠊ࢚ࢥ࣮ࡢᚅࡕ᫬㛫tEࠊᣑᩓಀᩘDࡀ኱ࡁ࠸࡯࡝ࡇࡢᘧ(1)ࡢῶ⾶⋡ࡣ኱ࡁࡃ࡞ࡿࠋ୍᪉ࠊࡑࢀ࡜ࡣ㛵ಀ࡞ࡃᶓ⦆࿴T2࡛ಙྕࡀῶ⾶ࡍࡿࡓࡵ࢚ࢥ࣮ࡢᚅࡕ᫬㛫ࢆ㛗ࡃࡍࡿࡇ࡜ࡣᚓ⟇࡛ࡣ࡞࠸ࠋࡑࡢࡓࡵ㟼☢ሙ໙㓄ࡀ኱ࡁ࠸࡯࡝ࡼࡾᑠࡉ࡞ᣑᩓಀᩘࡀ ᐃྍ⬟࡜࡞ࡿࠋ 25Υ࡟࠾ࡅࡿỈࡢᣑᩓ ᐃࢆࡲࡎ⾜࠸ࠊᘧ(1)ࢆ㐺⏝ࡋࡓࠋ⦪⦆࿴ࡢᚅࡕ᫬㛫ࢆῶࡽࡍࡓࡵ࡟
ᐃヨᩱࡢỈ࡟ࡣ◲㓟㖡ࢆ5 mMຍ࠼ࡓࠋ25Υ࡟࠾ࡅࡿỈࡢᣑᩓಀᩘࡣ2.310-9 m2/s࡛࠶ࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠾ࡾ8ࠊࡇࢀࢆ⏝࠸࡚ࠊ㟼☢ሙ໙㓄ࡢ㍑ṇࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝ㟼☢ሙ໙㓄ࡢ኱ࡁࡉࡣ78 T/m࡛࠶ࡾࡇࢀࡣ࣮࣍ࣝ⣲Ꮚ࡟ࡼࡿ☢ሙศᕸ ᐃࡢ⤖ᯝ࡜࡯ࡰྠࡌ࡛࠶ࡗࡓࠋ ୖグࡢタᐃ࡛㟼☢ሙ໙㓄ࢆ⏝࠸ࡓᣑᩓNMR ᐃࢆ⾜࠺࡜ࡍࡿ࡜ࠊෆᚄ1 mmࡢࢳ࣮ࣗࣈෆࡢヨᩱ࡛☢▼ഃ࡜ࡑࡢ཯ᑐഃ࡛☢ሙࡣ78 T/m*1 mm = 0.078T␗࡞ࡿࡇ࡜࡟࡞ࡿࠋࡇࢀࡣ1Hࡢඹ㬆࿘Ἴᩘ
࡛ࡣ3.32 MHz࡟┦ᙜࡍࡿࠋ୍᪉ࠊ8 Psࡢບ㉳ࣃࣝࢫࢆ౑⏝ࡋࡓሙྜࠊບ㉳ᖜࡣ1/(8 Ps) = 125 kHz࡜࡞ࡿࠋࡇࢀࡽࢆྜࢃࡏࡿ࡜NMRಙྕࢆບ㉳࡛ࡁ࡚࠸ࡿ✵㛫ࡢཌࡉࡣ125 kHz/3.32 MHz*1 mm = 38
Pm࡜࡞ࡿࠋࡋࡓࡀࡗ࡚ࠊRFࢥ࢖ࣝࡀᕳ࠿ࢀ࡚࠸ࡿ┤ᚄ1 mmࠊ㛗ࡉ2 mmࡢヨᩱ✵㛫ࡢ࠺ࡕᐇ㝿࡟
NMRಙྕࡀⓎ⏕ࡋ࡚࠸ࡿ✵㛫ࡣࠊFig. 3࡟♧ࡍࡼ࠺࡟ᖜ1 mmࠊ㛗ࡉ2 mmࠊཌࡉ38 Pmࡢ✵㛫࡜࡞ࡿࠋࡇࢀ࡟ࡼࡾࡓ࡜࠼ࡤບ㉳࿘Ἴᩘࢆ125 kHzኚ᭦ࡍࡿ࡜ࠊ㞄ࡢ38 Pmࡎࢀࡓ✵㛫ࢫࣛ࢖ࢫࢆ㑅ᢥ࡛ࡁࡿࡇ࡜࡟࡞ࡿࠋࡲࡓࠊ㧗㸦㉸ఏᑟࣂࣝࢡ☢▼࡛ࡣ☢ሙࡢ኱ࡁࡉࡸศᕸࡀ㠀ᖖ࡟Ᏻᐃࡋ࡚࠸ࡿ

ᗘ౫Ꮡᛶࠊ᫬㛫౫Ꮡᛶࡀ࡞࠸㸧ࡓࡵࠊᐃ୰࡟ࡇࡢࢫࣛ࢖ࢫ఩⨨ࡀࡎࢀࡿࡇ࡜ࡀ࡞࠸ࠋࡇࢀ

ࡽ࡟ࡼࡾࠊ㧗 ㉸ఏᑟࣂࣝࢡ☢▼ࡢ㟼☢ሙ໙㓄ࢆ⏝࠸ࡓᣑᩓNMR ᐃ࡛ࡣࠊ☢ሙ໙㓄᪉ྥ࡟㧗࠸✵㛫ศゎ⬟ࢆᐇ⌧࡛ࡁࡿࠋ ᐇ㝿ࡢᣑᩓNMR ᐃ౛ࢆFig. 4࡟♧ࡍࠋࡇࡇ࡛ࡣࠊ ᐃヨᩱ࡜ࡋ࡚ࢫࢡ࣮ࣟࢫ㸦◁⢾㸧50% w/wỈ⁐ᾮࢆ⏝࠸ࡓࠋࢫࢡ࣮ࣟࢫࡢ⃰ᗘࡀ㧗ࡃ࡞ࡿ࡜⢓ᛶࡀ㧗ࡃ࡞ࡿࡓࡵᣑᩓಀᩘࡀᑠࡉࡃ࡞ࡿࠋࡲ
ࡓࠊࡇࡢ≧ែ࡛ࡢỈࠊࢫࢡ࣮ࣟࢫࡢᣑᩓಀᩘࡢᩥ⊩್9ࡣࡑࢀࡒࢀ5.110-10 m2/sࠊ6.110-11 m2/s࡛࠶ࡿࠋᮏ◊✲࡛ࡣࢣ࣑࢝ࣝࢩࣇࢺࡀ

ᐃ࡛ࡁ࡞࠸ࡓࡵࠊ⁐፹ࡢỈ࡜⁐㉁ࡢ◁⢾ࢆ㆑ู࡛ࡁ࡞࠸ࠋ

ࡋ࠿ࡋࠊᣑᩓಀᩘࡢ㐪࠸ࡀ኱ࡁ࠸࡜Fig. 4࡟♧ࡍࡼ࠺࡟ᢡࢀ᭤ࡀࡗࡓ┤⥺࡜࡞ࡿࡓࡵࠊࡑࢀࡒࢀࡢ

－ 48 －

ᣑᩓಀᩘࢆồࡵࡿࡇ࡜ࡀྍ⬟࡜࡞ࡿࠋ ௒ᚋࡣ⿦⨨ࡢᨵⰋࢆ㐍ࡵࡿ࡜࡜ࡶ࡟ࠊ
ࡼࡾᙉ࠸☢ሙࢆHTSࣂࣝࢡ☢▼࡟╔☢ࡍ

6ROXWH:DWHU  PV
6ROYHQW6XFURVH    PVࡿࠋ☢ሙࡀᙉࡃ࡞ࢀࡤ㧗ឤᗘ໬㸦 ᐃ᫬㛫ࡢ▷⦰㸧ࡀᐇ⌧ࡍࡿ࡜࡜ࡶ࡟ࠊ㟼☢ሙ໙㓄ࡶ኱ࡁࡃ࡞ࡿࠋࡇࢀ࡟ࡼࡾᘧ(1)࡟♧ࡍࡼ࠺࡟ᣑᩓಀᩘࠊ᰾☢Ẽᅇ㌿ẚࠊT2ࡀᑠࡉ࠸ሙྜ࡟ᑐᛂ࡛ࡁࡿࡼ࠺࡟࡞ࡿࠋࡲ
ࡓୖグࡢࡼ࠺࡟✵㛫ศゎ⬟ࡀྥୖࡍࡿࠋ
ࡇࢀࡽࡢ≉ᚩࡣ7Liࡢᣑᩓ ᐃ࡟ࡼࡿࣜࢳ
࣒࢘࢖࢜ࣥ㟁ụࡢ㟁ᴟ㏆ഐࡢゎᯒ࡟฼⏝ྍ⬟࡛࠶ࡿ࡜⪃࠼࡚࠸ࡿࠋࡲࡓࠊ⢓ᛶࡢ㧗࠸࢜࢖ࣝࡸ⏕యศᏊ࡞࡝ࡢT2ࡢ▷࠸ヨᩱࢆ ᐃᑐ㇟࡜ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋ

Fig. 4. Measurement example of the mixture. The
signal intensity of diffusion measurement on 50%
w/w sucrosee:water solutions. The solid line isReferences

calculated from the reference value9.

(1) M. Takahashi et al., "NMR Relaxometry Using Outer Field of Single-Sided HTS Bulk Magnet Activated byPulsed Field," IEEE Transactions on Applied Superconductivity, vol. 32, no. 6, pp. 1-4, Sept. 2022, Art no.
4602404, doi: 10.1109/TASC.2022.3161247.
(2)T. Nakamura et al., “Development of a superconducting bulk magnet for NMR and MRI,” Journal ofMagnetic Resonance, vol. 259, pp. 68–75, Oct. 2015, doi: 10.1016/j.jmr.2015.07.012.
(3)E. O. Stejskal and J. E. Tanner, “Spin diffusion measurements: Spin echoes in the presence of a timedependent field gradient,” The Journal of Chemical Physics, vol. 42, no. 1, pp. 288–292, 1965, doi:
10.1063/1.1695690.
(4)B. Blümich, J. Perlo, and F. Casanova, “Mobile single-sided NMR,” Progress in Nuclear Magnetic
Resonance Spectroscopy, vol. 52, no. 4. pp. 197–269, May 2008. doi: 10.1016/j.pnmrs.2007.10.002.
(5)F. Casanova, J. Perlo, and B. Blümich, “Diffusion Measurements,” in Single-Sided NMR, Springer Berlin
Heidelberg, 2011, pp. 42–47. doi: 10.1007/978-3-642-16307-4.
(6)U. Mizutani, T. Oka, Y. Itoh, Y. Yanagi, M. Yoshikawa, and H. Ikuta, “Pulsed-field magnetization applied tohigh-Tc superconductors,” Applied Superconductivity, vol. 6, no. 2–5, pp. 235–246, Feb. 1998, doi:
10.1016/S0964-1807(98)00106-9.
(7)T. Oka, “Processing and applications of bulk HTSC,” Physica C: Superconductivity and its Applications, vol.
463–465, no. SUPPL., pp. 7–13, Oct. 2007, doi: 10.1016/J.PHYSC.2007.03.432.
(8)R. Mills, “Self-diffusion in normal and heavy water in the range 1-45.deg.,” The Journal of Physical
Chemistry, vol. 77, no. 5, pp. 685–688, Mar. 1973, doi: 10.1021/j100624a025.
(9)M. Rampp et al., “c,T-dependence of the viscosity and the self-diffusion coefficients in some aqueous
carbohydrate solutions,” Carbohydrate research vol. 328, no. 4 pp. 561-72, 2000, doi:10.1016/s00086215(00)00141-5－ 49 －

L1-3

Sec㠀౫Ꮡᛶ⭷⺮ⓑ㉁⭷ᤄධ࡟࠾ࡅࡿ኱⭠⳦⏤᮶⢾⬡㉁MPIaseࡢస⏝ᶵᵓࡢゎ᫂‫ۑ‬㔝ᮧ⸅㸪᳃⚈Ꮚ㸪኱⃝᭶✑㸪⸨ᕝ⣫ᶞ㸪すᒣ㈼୍2㸪ᓥᮏၨᏊ
1බ┈㈈ᅋἲேࢧࣥࢺ࣮ࣜ⏕࿨⛉Ꮫ㈈ᅋ⏕≀᭷ᶵ⛉Ꮫ◊✲ᡤ
2ᒾᡭ኱Ꮫ㎰Ꮫ㒊

Mechanism of action of MPIase, a glycolipid from Escherichia coli, in Sec-independent
membrane protein insertion‫ۑ‬Kaoru Nomura1, Shoko Mori1, Tsukiho Osawa1, Kohki Fujikawa1, Ken-ichi Nishiyama2, Keiko
Shimamoto1
1
Bioorganic Research Institute, Suntory Foundation for Life Sciences
2 Department of Biological Chemistry and Food Sciences, Faculty of Agriculture, Iwate University

An endogenous glycolipid, MPIase, in the Escherichia coli membrane regulates membrane protein
insertion cooperatively with proteinaceous translocons. Here, we focused on the Sec translocon-independent
pathway and examined the mechanisms of MPIase-facilitated protein insertion using solid-state nuclear
magnetic resonance and fluorescence techniques. Diacylglycerol, a trace component of E. coli membrane,
reduced the acyl chain mobility in the membrane core region and inhibited the insertion, whereas MPIase
restored them. Intermolecular interactions between MPIase and basic amino acids in the protein suggested
that the MPIase pyrophosphate attracts the basic residues of the protein toward the membrane surface, which
triggers the insertion. Thus, this study demonstrated the multi-faceted approach of MPIase to support
membrane insertion of proteins by using its unique molecular structure.
ࣜ࣎ࢯ࣮࣒࡛⩻ヂࡉࢀࡓ⺮ⓑ㉁ࡣ㸪Secࢺࣛࣥࢫࣟࢥࣥࡢຓࡅࢆ೉ࡾ࡚⭷ᤄධࡍࡿSec౫Ꮡ⤒㊰࡜ࠊSecࡢຓࡅ࡞ࡋ࡟⭷ᤄධࡍࡿSec㠀౫Ꮡ⤒㊰ࡀ࠶ࡿ㸬኱⭠⳦ෆ⭷࡟࠾࠸࡚ࡣ࡝ࡕࡽࡢ⤒㊰࡟࠾࠸࡚ࡶ㸪⭷࡟ᚤ㔞࡟Ꮡᅾࡍࡿࢪ࢔ࢩࣝࢢࣜࢭ࣮ࣟࣝ(DAG) (Fig. 1)࡟ࡼࡾᢚไࡉࢀࡓ⭷ᤄධࡀ㸪⢾⬡㉁MPIase (Fig. 1)࡟ࡼࡾಁ㐍ࡉࢀࡿ㸬ᡃࠎࡣࡇࢀࡲ࡛࡟ࠊSec㠀౫Ꮡᛶ⤒㊰࡟╔┠ࡋ㸪MPIaseࡸ
DAG࡟ࡼࡾᘬࡁ㉳ࡇࡉࢀࡿ⭷≀ᛶኚ໬ࢆゎᯒࡋ࡚ࡁࡓ1㸬ᮏ◊✲࡛ࡣ㸪ࡉࡽ࡟MPIase࡟ࡼࡾಁ㐍
ࡉࢀࡿSec㠀౫Ꮡ⺮ⓑ㉁ࡢ⭷ᤄධ࣓࢝ࢽࢬ࣒ࡢゎ᫂ࢆ⾜ࡗࡓ2㸬
Fig. 1. Structure of MPIase and DAG.
R=Ac or H, R’, R’’=C16:1, 16:0, 18:1,
18:0

Sec㠀౫Ꮡᛶࢱࣥࣃࢡ㉁⭷ᤄධ㸪ᅛయNMR㸪⢾⬡㉁‫ࡿ࠾࠿ࡽࡴࡢۑ‬㸪ࡶࡾࡋࡻ࠺ࡇ㸪࠾࠾ࡉࢃࡘࡁ࡯㸪ࡩࡌ࠿ࢃࡇ࠺ࡁ㸪࡟ࡋࡸࡲࡅࢇ࠸ࡕ㸪ࡋࡲࡶ࡜ࡅ࠸ࡇ

－ 50 －

ࡲࡎ㸪ศᏊ㔞ࡢᑠࡉ࠸␯Ỉᛶ⺮ⓑ㉁ࡢᅛయ
NMRࢆ⏝࠸ࡓ⭷ᤄධゎᯒἲ(Fig. 2)ࢆᥦ᱌
ࡋ㸪MPIase㸪DAG㸪ࡑࡋ࡚ྛ✀⭷⬡㉁ࡀ
⭷ᤄධ࡟୚࠼ࡿᙳ㡪ࢆホ౯ࡋࡓ㸬ࡉࡽ࡟㸪ྠᵝࡢ⭷⬡㉁࡛ᵓᡂࡉࢀࡓ⭷ࡢ⺯ගࢫ࣌ࢡࢺࣝࡸ⺯ග␗᪉ᛶ ᐃࢆ⾜࠸㸪⭷⾲㠃ࡢࣃࢵ࢟ࣥࢢࡸ⭷⬡㉁ࡢ࢔ࢩࣝ㙐ࡢ㐠ືᛶࢆゎᯒࡋ㸪⭷ᤄධຠ⋡࡜ࡢ┦㛵ࢆ⪃ᐹࡋࡓ㸬ࡑࡢ⤖ᯝ㸪⭷ᤄධࡣ⭷⾲㠃ࡢࣃࢵ࢟ࣥࢢ࡜⭷ෆ㒊ࡢ࢔ࢩࣝ㙐ࡢ㐠ືᛶ࡟ᙉ࠸┦㛵ࡀ࠶ࡾ㸪⭷⬡㉁ࡢ୺ᡂศ࡛࠶ࡿࣇ࢛ࢫࣇ࢓ࢳࢪ
࢚ࣝࢱࣀ࣮ࣝ࢔࣑ࣥ(PE)ࡸᚤ㔞ᡂศ࡛࠶ࡿ

Fig. 2. Procedure for inserting membrane proteins.

DAGࡣࡑࡢࢥ࣮ࣥᆺࡢศᏊᵓ㐀࡟ࡼࡾ⭷(top right) NMR spectrum of the pellet obtained fromෆ㒊ࡢ㐠ືᛶࢆ㍍ῶࡋ࡚⭷ᤄධࢆᢚไࡍࡿ

the procedure, showing both inserted and non-୍᪉㸪㏫ࢥ࣮ࣥᆺࡢMPIaseࡣ⭷࡟┦཯ࡍ

inserted protein signals.

ࡿᙳ㡪ࢆ୚࠼㸪⭷ᤄධࢆᅇ᚟ࡉࡏ࡚࠸ࡓ㸬ࡲࡓࠊ⭷⺮ⓑ㉁ࡢ⭷ᤄධ⌧㇟ࡣ㸪⭷ࡢ≀⌮໬Ꮫⓗ࡞ᛶ㉁ࡔࡅ࡛࡞ࡃ㸪MPIase࡜ᇶ㉁⺮ⓑ㉁ࡢ㛫ࡢศᏊ㛫┦஫స⏝࡟ࡶ㛵ಀࡋ࡚࠾ࡾ㸪MPIaseࡢ㈇㟁Ⲵࢆᣢࡘࣆࣟࣜࣥ㓟ࡀᇶ㉁⺮ⓑ㉁ࡢṇ㟁Ⲵࢆᣢࡘࣜࢪࣥࡸ࢔ࣝࢠࢽࣥࡢഃ㙐࡜㟼㟁ⓗ࡞┦஫స⏝ࡍࡿࡇ࡜࡛㸪⭷ᤄධࡢึᮇẁ㝵࡛⺮ⓑ㉁ࢆ⭷㏆ഐ࡟ᘬࡁᐤࡏ࡚࠸ࡓ㸬௨ୖࡢᵝ࡟㸪MPIaseࡣࡑࡢࣘࢽ࣮ࢡ࡞ศᏊᵓ㐀࡟ࡼࡾ㸪⺮ⓑ㉁ࡢ⭷ᤄධࢆᵝࠎ࡞ᙧ࡛ᨭ࠼࡚࠸ࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓ(Fig. 3)㸬

Fig. 3. Schematic model of the membrane insertion of a small hydrophobic substrate protein in
E. coli membranes.

References(1) Nomura, K. Yamaguchi, T., Mori, S., Fujikawa, K., Nishiyama, K., Shimanouchi, T., Tanimoto, Y., Morigaki,K., Shimamoto, K. (2019) Alteration of Membrane Physicochemical Properties by Two Factors for Membrane
Protein Integration. Biophys. J. 117, 99-110.
(2) Nomura, K., Mori, S., Fujikawa, K., Osawa, T., Tsuda, S., Yoshizawa-Kumagaye, K., Masuda, S., Nishio,
H., Yoshiya, T., Yoda, T., Shionyu, M., Shirai, T., Nishiyama, K., Shimamoto, K. (2022) Role of a bacterial
glycolipid in Sec-independent membrane protein insertion. Sci Rep. 12, 12231.

－ 51 －

L1-4

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.3!3).-/!33%1-2.&!1.4-$3(%3)+3%$!7)2."3!)-%$&1.,3(%.&!+!-)-%!++.6%$#.,/+%3%
$%3%1,)-!3).-.&3%-2.1k@MIĤĥHXDV4ăÇ1"ĦÉ/ ğá ® ©.10ħ
HXDV!Ħ>J7TYEYf OWYNöÄ4ąøĦĠíç  çbċĤöÄċĥ/öÄ4ĊĦ@MI ĤöÄ¶KEYXĥ4āÙ0Õ10ħ öÄÖ!HXDV ^p^ċ¿4wÕ 0Å|´Ö0 Ħ»,,?6B ¤öÄ «ĀÐÜ4µħZ¿Ħ³!1%ĦćĊí-/[ÑsĒ`ċ­ĤíßHXDV ^p ĥ ªöÄìÎû ÿkĤ!'-%3)#!++81)%-3%$)#1.#1823!+++!8ĥ Ħ;,?6B ªöÄ . 
HXDVÕÅ04îħ.ĦĆ¼ćĊúkOWY

N4ėåĦ×k]ªöÄ4[ÑsíĒíĒªöÄ±ÚkĤ!'-%3)#!++81)%-3%$)#1.#1823!+42/%-2).-ĥĦk4ì0 )-2)34öÄ¶KEY
X4āÙ0)²}0ħ  .Ħ1%lþOWYN!ćĊċĤĥ çb¿1 /ĦāÙúöÄ¶KEYX!ċ/ )Ě.1ħÖ-/HXDV4wÕ0(!ĦÔ0  íċ/4
'  ¶KEYX4©0 Ħ) !ċ4ZÃæçb¿ ..ZüĂ/ ¶KEYX4©0«Ā 0ħ 
³!Ħ¨ù 5OWYF4·âĦ ( ćĊċ4ÙÃ &r½ú`ċOWYN4¾ėåħOWYN-/ªöÄ±Úk . HXD
V wÕ4Ć&0)Ħ`ÑsÖ õ&3-0¬â¢ė ú­4¸ôħ[ÑsíĒOWYNĦªöÄ±Ú×Ħ@MIHXDV &/,Ħ*!*Ħ %#2Ħ3%#Ħ + 

－ 52 －

`ċOWYN!Ħ  ,,`ēxģOWYN4ºďlþĤ)' ĥħĆ¼ñ
ĕċ4 çbćĊĦg¯

E6SX<ćĊċ4r½úÏÌħÙ

(

íê

-${u

Ą!Ħ  9âĈh¡íêĤ   ĥ{uĄ4mâħ5UJ
XªöÄ ±Ú×Ĥ 63  kò¦ !2ĥ
49UAĆ¼ñ vOWYNyCG
IĦí\ĘÐ ćĊĤ 1/, $+0+#.,$/+"0$!3$+(!* 0$!$! +"0$!
!2!(+,! ,.+!

 :Ċ ¿ 2qÒĥ4~ªö
Ä4[ÑsĒħ  !ĦªöÄ![ÑsĒÞ°Ć¼ñĤkĥ)ćĊÞ°0ħĦ ĒªöÄ ċ Ă ĜćĊċ4 :r½Ħk Ù4ýħä0Ù4÷/čĦZĐ AQ;IV4 ĝħ©.1k AQ;IV4)' îħ[ÑsíĒ-/tĔ x
ģLY; Ëz1ĦoAQ;IVKEYX 0Í ÂéāÙ1ħ
öÈ!r½Ă :/ öÄ¶KEYX ©.14¯0ħKEYX ăÇ ö
ÈĦ8VR:@ÛóHXDV4wÕ0²}ħ`ÑsÖ4âĢ!Ħ8VR:@Ûó  UPV15UJXªöÄ ±Ú×4mâĦćĊċĤ ĥ!r½ĦØÃĘĤ ,2ĥ 0Ć¼ñ Ċ-/
40ä0Ęħ)' èęAQ;IV4āÙn4îħØÆ

0

i

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5OWYF @MI  ĎĉÅ0î1ħ /,!0.+" +" (*%*! 1* !. %*0!.)%00!*0 .+00%+* %* %0!/ 0$! %.!0%+* +" 0$! 4%/
3%0$.!/,!00+ &1/0!"+.!,,(5%*#
0$!0!),+.(0%(05 6 7 +..!(0%+* /,!0.+" +" (*%*!+0%*! 5/0.0%*# 0$!/!-1!*!0   6 *    6 $!/),(!
01!3/ .+00! 5 6 1.%*#0$!)%4%*#0%)!+" )/  5"!          1/1)%!0      1/1)%!0(       '!       
$!.3++ !0(    

－ 53 －

L1-5








  ÙÂpÑ Ø Ã²Ë´º Ø Ó{YÓ¯v´ºJXLZ       





*#/.0 &$ *.#$($#$0%$2-       

         #1  ) 1 '*+$)"( /#*.)$)./-0( )/.!*-#$"#!$ '  0'/-'*2/ (+ -/0-  
("$)"' .+$))$)"3)($)0' -+*'-$4/$*).+ /-*.*+3*($)$)"/# 
'*. 3' # '$0()-3*" )$.$")'+- (+'$!$/$*)/ #)*'*"$ ./# /*/'. ).$/$1$/3"$)*!
5 $.)*2-*0/$) '3#$ 1' +1$)"23/*#$"#. ).$/$1$/3$) ''./-0/0-'./03*!( (-) +-*/ $).)(3'*$!$-$'.)/# +- . )//$*)2 $.0..*0--  )/ !!*-/.*)$./-0/0-')'3.$.*!0)' ' *(+*0).)+-*/ $).$$))*$(*). +*'-$4$)"" )/.!*-$) ''$$$&"-*0)
.0++- ..$*) / #)$,0 . 0.$)" /#  ($-*21  !- ,0 )3 (*0'/$*) ) $1 )'3.$. *! +-*/ $).
*)!*-(/$*) ). (' $)3)($ ,0$'$-$0(m³¡i£§9ÛHOX8Þ%i£B¡HO(a)

X7¸-+548B)*t[4)@qÁ8

Backbone(>NH)

Lysozyme

Arg(>NH)
Arg(-NH2, =NH2)$@Ä4$@(Þ¶|^48l­`\(wÝ4$5.4kHz@ !9+A:47RUDSBÈ8yÎ5go7°%@"£`©§#BÖÞ¶|^4<Þ%

Lys(-NH3) **j(>A@+5B·,0  :06RUD

His15

SB¨Ê/.7£`©  BÔ7 ®4)@"fÕyÍ#QWZP5ÈyÎGHMSBÖ±(b)Þ¶|^7'%3<l­B¿,22ÅÚ6i

MexX½8~¦eiÆªBqÁ7,0  ÕyÍyÎG
HMS8"?EH#4br¢hxBgo,b r } **

5NCIkB]¼4)@+5<·,0 

図１ 非標識リゾチーム (a)と MexX 沈殿(b)のDNP 増強15

1

N-交差分極スペクトル (黒)と H-

dephased スペクトル(灰)。T = 30 K, vR = 8.9
115

kHz。インセットは可変時間 H- N CP で得た分極成長カーブの FT。+A

> B a /  ® ¬ 4 À s   j  9  ^  Þ ¶ |   YÞ i Æ Á  ^ 4 c B Ì & 0
t[8;6>.Þi£¡HOX«8"Þ©Ï_8µA#B¹£³7j°-@HOXi£8¾dÇª§ =TKHFZV»×Ò³ÞnÄ <Ö±,0   9¦8+572%3Ð($1084{u-@ Ü¤É¥i=Ã²ËÈ8ÇªßzÞ%Óe¯u\ß\&1»Âa¯uÞ4<y§/.7£6¯ZiBÞi£n4)@Åßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßßm³¡i£§Þ¶|Y£`©^J<@:ÉÈyÎ»Âa :2) 4&2+5> 5,;/

－ 54 －

Ù]ÜCN>CMLXBi£d

蛋白質構造と化学シフト
データベース

JC:W¦m¦8vÌ5,A7X&Ìi£
8£vnBj°,0Ábr¨hYCN＋薬剤 B»×Ò  § m³Ä¬7

＋薬剤 B

＋薬剤 A

新しい計算
科学的解析法

$@Ã²Ë8Ñ6X;XPV8Æ§5 ¨¨´i× BW@QP@A

構造平衡 B＋薬剤 A
構造平衡 A

a#GD:PCX8Ñi~´º  Þ¶|  §7413  8(²
図 2 構造分布の変化を NMR 信号形状の解析から逆算する。
c87Z>Z4t[-@5¯Z½  È
平衡にある構造を凍結し、信号形状から主鎖ねじれ角(φ,ψ)ª7Ú5À&>A3)0kYZ¤É6,7
の分布と占有数の変化に結びつける。例えば、結合薬剤ごと
x«zq¡   
8  brの GPCR の構造アンサンブルを決定、比較できる。
4¥i=Ã²Ë8Æ(4)@qÁ($@¾Û¾y§49Ñ(i~,0i½8Æ9pØ4$@,¢ºpY¿8¤<Ø,% '> 9´Æ³6f_Æ8Q256@ z 7·-89,AAÝgU=?ZS  ¸4  ½ÈE:MU68~dhIXQÃ²Ë ß  ¸4 Þ8¥ È8  HH:AV4$@  59NUZ8©l<l30Àsj9,A-A   c  c4 HH:AV6> i HH:A
V49  i·8¹¸4ei6  (>A0 U=?ZSnQ8FH?<X ^Ö8 br(    WÏ7Èª*A3'? t($@55'@ GGAd'>  9
多次元 NMR 信号(QWAXn,0$rUv±Z4$?qvÊ×  §'>  Ï×9 " 5Çª4)0 ¢ºpY¿8¹|¤7p®³6Ë}(2):5&Û¾y§JC:W 5¼;s5/\&1Ãd%Ã²Ë×8¢º½sLZB¤607°-@Ç°. ®¬49  .(4fZ³6¼ZÑÆ:49Ø,% (t)58T¦Ñi~QÔt8^Ö8Õ^
Ö6KNt8QWAXn¬60(Ñi~($13<¤4)@ :0Ñ8SA0Ûs=¢ºpY¿8{(iA@ª4¬«8Î­(qÁ4$@ m³Ä7$@Ã²Ë8Ñ6X;XPV¤§<Ö±R4$@z  Ñi~Bµ×c½, br8¬'>Ñ6X;XPVB-@§4©¨  ¾y! 46:
JH4)6% {(\&1»Âa4³i4)@ Ñi~8m³ÄBj°,0KGA4QWKH8H6¥Á±®9 Ã²Ë`j{Z~d½sÎbo6KWCB¾¿8¾¿¡wÛs604*Ç>AÃ²Ë[m¥8Ò³6HAOM<Z8Q2'<,A6%+8VCN>C6LXB  §Á¨hÄ6072% 3<8ÐB{u-@ ­      !!        

                  !          
ÍÐ´º9¶Ä ¥YÔ¶  ´ºt `°YQO@AGZS ¶´ÊYt

Ã²Ë´ºYiÖ±QWOS74@Bj(35A0 － 55 －

     

L1-6



    







© Ã¦ ß/&$ ( ,5)-  e }Ã ( ( $%  )** & 3,.$&#( &$0$ ,!)(   ( /&')/, /2
³£Á¾y¸½ Ç uÀy¸½WbXc" # 
 " # 
" #!!         









 ! 







 $,)%$"-#$' /&$ (,5)- )-#$#$,))( )** &(($%3,.$&#( 

&$0$ ,!)( (/&')/, /2  #      #   #   " #   " # 







 !  

" #!!

3('$(/& ,*)&,$4.$)(-/,!  (#( -* .,)-)*3  $-*)1 ,!/&. #($+/ .#.((&34 .# -/,! -.,/./, )!$(),"($(()'. ,$&-(.# )- ,0.$)()!+/,/*)&,(/& $$-$(", . '(  (.&31 #0 -#)1(.#.  (*)&,$4.$)(.,(-! ,!,)' .)+/,/*)&,
(/& $ 0 ($(&)1"''(),$-.(.(/& $, 1 , *),..# )- ,0.$)()!( ($((!),

.# !$,-..$' ().# ,$--/ $-.)).$(#$"#, -)&/.$)(-* .,)!+/,/*)&,(/& $1$.#  , .# )'$(.$)()!  (- +/ ( -)0 ,)' -.#$-*,)& '(**&$ -$..)- 0 ,&
(()'. ,$&-"''&/'$((((),3-.&-(,$.&3-.-( $.&3-.-iÇ 324gÂ%MLZ[¡5±4/¡5ÂÛ4&+±¶3¥Ï6ª¶3rO.$MJ5Z[¡5ÂÛ¥Ï1±15·ÙO²Æ&+d0¶º3¡ÊÈOÐDL$16ÔÄ0L*5+DÂÛ¥ÏOvVSc`a]`0Ì<L§5µ
6$M JEZ[¡»OÐ%)LÖ13Li NMR 6f5pn«1¨</!h#s/ÂÛOÒ¶4Å®!0"3+D4Z[¡5ÂÛ¥Ï5Å®46>1P2q´%M/$3 -+ÍhOo(L«1&/t¶¢l¤ÝDynamic Nuclear Polarization:DNPÞOq´&+i NMR 5«!µ&+[1]DNP-NMR 6_UQ`¯ OË4sL$1
0_UQ`p!ËÂÛÍm4&ÂÛOÒ¶4Üu0"L_UQ`  ¯
1H ¢  ÂÛÅ®¢5­M0ÂÛ NMR kxOÅ®(L«6 DNP Surface-Enhanced NMR

Spectroscopy (SENS)1|7M/L( 1a)[2]  DNP-SENS %" 13C, 15N, 29Si

0>', I =A/B!'093 *I > 1/2 $1'093<4?   $1'0#.)7 75%5 17O 6@2;:/=8
!'0&+(!'0& DNP-NMR <4-  
1H 1~¤¢Ø5p¤¼t4&/6 DNP-SENS 4Ñ&+&p¤¼t« Adiabatic
D-RINEPT O×µ&+$1Oz&/"+( 1b)[3]Adiabatic D-RINEPT 6$MA0Ú,-+
DNP-SENS 4ILh{¬~¤¢5Å®Ow¿4&+         
3!&A8N"1M?(#'HKP$PI&8N$-=LG4-#
cPBL/cLJ:PK9CLc'FP@cL－ 56 －

%J46 Adiabatic D-RINEPT 4 Multiple Quantum (MQ) MAS OÎs&+ D-RINEPT-MQMAS
TcSbVO×µ&DNP-SENS 4IL~¤¢5 MQMAS V^RY`5®«O ISMAR 0
z&+( 1c)µÂ06dÉ\`VTcSbVOj´&+ DNP-SENS 5ÕÓu°GÕ¹u°;5´Oz(LAdiabatic D-RINEPT 06$MA0ÕÓu°5 DNP-SENS V^RY`OÅ®&/"+!
$M4s
e6 Cd  c5Y1&/3 ZnS Z[5 67Zn 1 33S 5 DNPSENS V^RY`5Å®Oz(LA+D-RINEPT-MQMAS ®06-Al2O3 `V SiO2 O6'DY4j´%MLT`b  ZnO 4s5 ZnO Z[
5 17O MQMAS 5Oz(L*5fyÕÓu°1&/SiO2-Al2O3 I9(ZrO2ZnO)/SiO2 5 17O MQMAS ®O(Figure 1. (a) DNP-SENS and Pulse sequence diagram of (b) Adiabatic D-RINEPT-QCPMG and (c) DRINEPT-MQMAS-QCPMG.
%()1& " ' (.
¸½6 JSPS »¸ JP 20K15319 5 O +E50( ! , ( [1] K.-N. Hu., et al. J. Am. Chem. Soc., 2004, 126, 10844–10845.
[2] A. Lesage., et al., J. Am. Chem. Soc., 2010, 132, 15459–15461.
[3] H. Nagashima., et al.J. Am. Chem. Soc., 2020, 142, 10659–10672.

－ 57 －

L2-1

ࢩ࢔ࣀࣂࢡࢸࣜ࢔ࡢගࢭࣥࢧ࣮࡟࠾ࡅࡿ⬺ࣉࣟࢺࣥ໬ࡋࡓ
ሷᇶᛶ࢔࣑ࣀ㓟ࡢほ‫ۑ‬ỌỤᓠᖾ㸪㣤ሯభ௓㸪㟷ᒣὒྐ㸪ᐑࣀධὒᖹ㸪⚄㔝ᬛྖ㸪ఀ⸨㝯㸪ᗈ℩ౡ㸪୕ᓥṇつ11ᮾி⸆⛉኱Ꮫ࣭⸆Ꮫ㒊
2኱㜰኱Ꮫ࣭⺮ⓑ㉁◊✲ᡤ3ᰴᘧ఍♫CRYO SHIP
4ᮾி㒔❧኱Ꮫ࣭⌮Ꮫ◊✲⛉
5㇏ᶫᢏ⾡⛉Ꮫ኱Ꮫ࣭ᕤᏛ◊✲⛉Observation of a deprotonated basic amino acid in a cyanobacterial photosensor
żTakayuki Nagae1, Yusuke Iizuka1, Hiroshi Aoyama1, Yohei Miyanoiri2, Satoshi Kamino3, Yutaka Ito4, Yuu
Hirose5, Masaki Mishima1
1

Department of Pharmacy, Tokyo University of Pharmacy and Life Sciences

2

Institute for Protein Research, Osaka University

3 CRYO SHIP Incorporated
4 Graduate School of Science, Tokyo Metropolitan University
5 Graduate School of Engineering, Toyohashi University of Technology

Cyanobacterial photosensor proteins have a chromophore, phycocyanobilin (PCB), and exhibit a wide
range of absorption wavelengths ranging from UV to far-red light. The cyanobacterial photosensor protein
RcaE reversibly converts between green and red-absorbing states. To elucidate the mechanism of thisabsorption wavelength tunning, we are studying its structural features and protonation state using NMR
spectroscopy and X-ray crystallography. Recently, we have determined the structures of RcaE in both green
and red absorbing states at 1.63 and 1.75 Å resolution, respectively. Furthermore, we succeeded in direct
observation of the deprotonated amino group of a lysine residue neighboring to PCB. We have found that
deprotonated amino group (-NH2) of a lysine. ThisPr form

Pg form

is the first report of the direct observation of
deprotonated lysine inside a native protein structure.
ࢩ࢔ࣀࣂࢡࢸࣜ࢔ࡢගࢭࣥࢧ࣮ࢱࣥࣃࢡ㉁PCB

ࡣⰍ⣲ࣇ࢕ࢥࢩ࢔ࣀࣅࣜࣥ(PCB)ࡢ⤖ྜ࡟ࡼࡾ㸪⣸እග࠿ࡽ㐲㉥Ⰽගࡲ࡛ᗈ⠊࡞ᴟ኱྾཰Ἴ
㛗ࢆ♧ࡍ㸬ࢩ࢔ࣀࣂࢡࢸࣜ࢔ࡢගࢭࣥࢧ࣮ࡢ1
ࡘ࡛࠶ࡿRcaEࡣ⥳Ⰽග྾཰ᆺ(Pg)࠾ࡼࡧ㉥Ⰽග྾཰ᆺ(Pg)ࡢ஧≧ែ㛫ࢆྍ㏫ⓗ࡟ගኚ᥮ࡍࡿ
ࡀ㸪ࡇࢀ࡟ࡣPCBࡢ⬺ࣉࣟࢺࣥ໬㸭ࣉࣟࢺࣥE217

Fig. 1. Structures of RcaE in the Pr and Pg
forms. Photoisomerization induces a positionalchange of PCB in the binding pocket.

⬺ࣉࣟࢺࣥ໬ࣜࢩࣥ㸪ගࢭࣥࢧ࣮㸪ࢩ࢔ࣀࣂࢡࢸࣜ࢜ࢡ࣒ࣟ
‫ࡁࡺ࠿ࡓ࠼ࡀ࡞ۑ‬㸪࠸࠸࡙࠿ࡺ࠺ࡍࡅ㸪࠶࠾ࡸࡲࡦࢁࡋ㸪ࡳࡸࡢ࠸ࡾࡼ࠺࡬࠸㸪࠿ࡳࡢࡉ࡜ࡋ㸪࠸࡜࠺ࡺࡓ࠿㸪ࡦࢁࡏࡺ࠺㸪ࡳࡋࡲࡲࡉࡁ

－ 58 －

໬ࢆక࠺ࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠸ࡿ1㸬ࡇࡢ྾཰Ἴ

(a)㛗ኚ᥮ࡢ࣓࢝ࢽࢬ࣒ࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵ㸪ᡃࠎ
ࡣNMRศගἲ࡜X⥺⤖ᬗᵓ㐀ゎᯒἲࢆ⏝࠸࡚ගࢭࣥࢧ࣮RcaEࡢᵓ㐀ⓗ≉ᚩ࠾ࡼࡧࣉࣟࢺࣥ
໬≧ែࡢゎᯒࢆ㐍ࡵ࡚࠸ࡿ㸬ࡇࢀࡲ࡛࡟Pr࠾ࡼࡧPgࡢ୧≧ែ࡟ࡘ࠸࡚1.63 Å࠾ࡼࡧ1.75 Åࡢ㧗ศゎ⬟࡛⤖ᬗᵓ㐀Ỵᐃ࡟ᡂຌࡋ࡚࠸ࡿ㸬ゎᯒࡢ⤖ᯝ㸪ග྾཰࡟ࡼࡗ࡚PCBෆࡢ஧㔜⤖ྜࡀZ/E␗ᛶ໬ࡋ㸪ࡑࢀ࡟క࠸PCBࡢ఩⨨ࡀGAFࢻ࣓࢖ࣥෆ࡛኱ࡁࡃ⛣ືࡍࡿࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗࡓ

(b)(Fig. 1)㸬ࡇࡢPCBࡢ⛣ືࡣ㸪E217࡞࡝྾཰Ἴ㛗ࢳ࣮ࣗࢽࣥࢢ࡟㔜せ࡞࢔࣑ࣀ㓟ṧᇶ࡜ࡢ┦஫స⏝ࢆ኱ࡁࡃኚ࠼ࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓ㸬ࡋ࠿ࡋ࡞ࡀࡽ㸪RcaEࡢග྾཰ࡢ㘽࡛࠶ࡿỈ⣲ࡣX⥺⤖ᬗᵓ㐀ゎᯒ࡛ࡣゎᯒᅔ㞴࡛࠶ࡿ㸬ࡑࡇ࡛
PCBࡢ࢔࣑ࣀᇶࡢ15N┤᥋ᐃࢆ⾜ࡗࡓ㸬ࡑࡢ⤖ᯝ㸪Pr࡛ࡣ4ࡘࡢ❅⣲ཎᏊ඲࡚ࡀ⬺ࣉࣟࢺࣥ໬ࡋ࡚࠸ࡿࡇ࡜㸪Pg࡛ࡣ4ࡘࡢ❅⣲ཎᏊࡢ࠺ࡕ
1ࡘࡀ⬺ࣉࣟࢺࣥ໬ࡋ࡚࠸ࡿࡇ࡜ࡀᐇ㦂ⓗ࡟᫂ࡽ࠿࡟࡞ࡗࡓ2㸬
ࡉࡽ࡟㸪PCBࡔࡅ࡛ࡣ࡞ࡃࢱࣥࣃࢡ㉁ഃࡢ

Fig. 2. Detection of Lys-NH2 (a) 1H-15N HSQC

NMRࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓ⤖ᯝ㸪PCBࡀ⬺ࣉࣟ

spectrum of 15N labeled RcaE. (b) Close up view ofࢺࣥ໬ࡋ࡚࠸ࡿPg࡟࠾࠸࡚㸪≉␗࡞໬Ꮫࢩࣇࢺ

the signal in (a) without 1H decoupling.

ࡢNMRಙྕࢆほࡋࡓ(Fig. 2(a))㸬ࡇࢀࡣPCB㏆ഐ࡟Ꮡᅾࡍࡿࣜࢩࣥṧᇶࡢഃ㙐࢔࣑ࣀᇶࡀ㟁Ⲵࢆࡶࡓ࡞࠸NH2ᆺࡢ≧ែ࡟࠶ࡿࡇ࡜࡟⏤᮶ࡍࡿ㸬ࡇࡢࡇ࡜ࡣHSQCࡢ15N㍈ࡢศ⿣࠿ࡽࡶ☜ㄆ࡛ࡁࡓ(Fig. 2(b))㸬⯆࿡῝࠸ࡇ࡜࡟㸪PCBࡀࣉࣟࢺࣥ໬
ࡋ࡚࠸ࡿPr࡛ࡣ㸪ࡇࡢLys261ࡢഃ㙐࢔࣑ࣀᇶࡣ㏻ᖖࡢNH3+ᆺ࡟࡞ࡗ࡚࠸ࡓ㸬ࣜࢩࣥࡀ୰ᛶࡢNH2
ᆺࡢ≧ែ࡟࠶ࡿࡢࡣᴟࡵ࡚⛥࡛㸪␯Ỉᛶࢥ࢔࡟ேⅭⓗ࡟࢔࣑ࣀ㓟⨨᥮ࢆᑟධࡋࡓேᕤࢱࣥࣃࢡ㉁࡟࠾࠸࡚ࡑࡢᏑᅾࡀሗ࿌ࡉࢀ࡚࠸ࡿࡢࡳ࡛࠶ࡾ3㸪ኳ↛ࡢࢱࣥࣃࢡ㉁࡟࠾࠸࡚NH2ᆺࡢࣜࢩࣥࢆᐇ
㦂ⓗ࡟┤᥋ほࡋࡓࡢࡣᮏ◊✲ࡀึࡵ࡚࡛࠶ࡿ㸬ࡲࡓ㸪13CHᶆ㆑ࢆ᪋ࡋࡓࣜࢩࣥ(SAIL)ࢆ⏝࠸࡚㸪

1D 13C ᐃ࡟ࡼࡾྠ఩యࢩࣇࢺࢆほ ࡍࡿࡇ࡜࡟ࡼࡗ࡚㸪NH3+࡜NH2ࢆ༊ูࡍࡿᡭἲ4ࢆ㐺⏝ࡋࡓ࡜ࡇࢁ㸪☜࠿࡟Pg࡛ࡣNH2ᆺ࡜࡞ࡿࡇ࡜ࢆ☜ㄆ࡛ࡁࡓ㸬
References[1] Hirose Y., et al. (2013) Proc. Natl. Acad. Sci. U. S. A. 110(13), 4974. [2] Nagae T., et al., (2021) Proc.
Natl. Acad. Sci. U. S. A. 118(20), e2024583118. [3] Takayama Y, et al., (2008) J Am Chem Soc. 130(21),6714. [4] Takeda, M., et al. (2021) Magn. Reson., 2(1), 223.
ㅰ㎡
ᮏ◊✲ࡢከḟඖ NMRᐃࡣ㸪ᩥ㒊⛉Ꮫ┬ඛ➃◊✲ᇶ┙ඹ⏝ಁ㐍஦ᴗࠕNMR ඹ⏝ࣉࣛࢵࢺࣇ

࢛࣮࣒ࠖ(⌮◊ᶓ὾)࡜⺮ⓑ◊ᣐⅬ஦ᴗ NMR ඹྠ฼⏝◊✲࡟ࡈᨭ᥼࠸ࡓࡔࡁࡲࡋࡓ㸬 SAIL ἲࡣ⏥ᩫⲮṇᜏ ᮾி㒔❧኱Ꮫྡ㄃ᩍᤵ࡟ࡈᨭ᥼࠸ࡓࡔࡁࡲࡋࡓ㸬－ 59 －

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5HIHUHQFHV>@<DPDRNLet alPhys. Chem. Chem. Phys  >@<DPDRNLet alBiophys. Rev  >@
6DNDPRWRet alChem. Commun  － 61 －

L2-3

࣓ࢳ࢜ࢽࣥഃ㙐࣓ࢳࣝᇶࡢಙྕほ ࡟ࡼࡿ⣽⳦࡭ࢇẟ࣮ࣔࢱ࣮
ᅛᐃᏊࡢNa㸩࢖࢜ࣥ⤖ྜ࡟ࡼࡿᵓ㐀ኚ໬ࡢゎᯒ‫ۑ‬㘊㔝㐩㑻㸪ᑠᔱㄔྖ2, ᮏ㛫㐨ኵ2, ᐑࣀධὒᖹ㸪1኱㜰኱Ꮫ࣭⺮ⓑ㉁◊✲ᡤ2ྡྂᒇ኱Ꮫ࣭⌮Ꮫ◊✲⛉࣭⌮Ꮫᑓᨷ࣭⏕࿨⌮Ꮫㅮᗙ

Na+-induced structural dynamics of the PomAB flagellar stator complex, observed by thespectra of methyl 13C in methionine residues.
‫ۑ‬Tatsuro Nishikino1, Seiji Kojima2, Michio Homma2, Yohei Miyanoiri11Institute for Protein Research, Osaka University

2 Division of Biological Science, Graduate School of Science, Nagoya University

The bacterial flagellar motor consists of the rotor and stator, and their interaction is essential to generate
torque. The stator in marine Vibrio is made up of two membrane proteins, PomA and PomB, and functions
as a sodium ion channel. We recently performed structural analyses by single particle cryo-EM andrevealed that five PomA and two PomB molecules form the single stator complex, although the mechanismof sodium ion flux is still unclear. To clarify this, we analyzed structural dynamics of PomAB complex
induced by sodium ion binding, using solution NMR. We prepared the stator proteins labeled with methyl
13C in methionine residues and measured 1H-13C HMQC spectra with or without sodium ion, and found thatchemical shift change occurred in several signals. To assign the signals, we have replaced each methioninewith isoleucine or leucine, prepared proteins and measured their spectra. Based on the results from thosemeasurements, we will discuss the structural dynamics of the stator induced by sodium ion binding.
⣽⳦ࡢ࡭ࢇẟࡣࠊᅇ㌿࣮ࣔࢱ࣮ࢆᣢࡘ㉸ศᏊ」ྜయ࡛࠶
ࡿࠋ࣮ࣔࢱ࣮ࡣࠊ⭷ෆእ࡟ᙧᡂࡉࢀࡿ㟁Ẽ໬Ꮫ࣏ࢸࣥࢩࣕ
ࣝᕪࢆ㐠ື࢚ࢿࣝࢠ࣮࡟ኚ᥮ࡍࡿࡇ࡜࡛ᅇ㌿ࡍࡿ (1) ࠋࡇࡢ࢚ࢿࣝࢠ࣮ኚ᥮ࡣࠊᅇ㌿Ꮚ (Rotor) ࡢ୍㒊࡛࠶ࡿ C-ring࡜࢖࢜ࣥࢳࣕࢿࣝ࡜ࡋ࡚ᶵ⬟ࡍࡿᅛᐃᏊ」ྜయ (Stator) ࡢ࢖࢜ࣥὶ࡟ඹᙺࡋࡓ┦஫స⏝࡟ࡼࡗ࡚⏕ࡌࡿ (Fig. 1) ࠋᾏὒᛶࣅࣈࣜ࢜⳦ Vibrio alginolyticus (V. alginolyticus) ࡢᅛᐃᏊ」ྜయࡣࠊྠࡌ࢜࣌ࣟࣥ࡟ࢥ࣮ࢻࡉࢀࡓ 2 ✀㢮ࡢ⭷ࢱࣥࣃࢡ㉁ [PomA, PomB] ࠿ࡽ࡞ࡿࠋ኱⭠⳦ࡸࣅࣈࣜ࢜⳦ࡢ
⢭〇ࡉࢀࡓᅛᐃᏊ」ྜయࡢ⏕໬Ꮫⓗ࡞ゎᯒ࠿ࡽࠊ」ྜయ୰
ࡢ A ࢧࣈࣘࢽࢵࢺ࡜ B ࢧࣈࣘࢽࢵࢺࡢศᏊẚࡣ 4:2 ࡛࠶ࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡓࠋࡋ࠿ࡋࠊ 2020 ᖺ࡟ PomA/PomB࡜┦ྠᛶࡢ࠶ࡿ Campylobacter, Clostridium, Bacillus ࡢ MotA/MotB 」ྜయࡀ 5 ศᏊࡢ MotA ࡜
2 ศᏊࡢ MotB ࠿ࡽᡂࡿࡇ࡜ࡀࢡࣛ࢖࢜㟁Ꮚ㢧ᚤ㙾ࢆ⏝࠸ࡓ༢⢏Ꮚゎᯒ࡟ࡼࡾ᫂ࡽ࠿࡟࡞ࡾࠊ
MotB ࢆ㍈࡜ࡋ࡚ MotA 5 㔞యࡀᅇ㌿ࡍࡿࡇ࡜࡛ C-ring ࡜┦஫స⏝ࡋ࡞ࡀࡽ࢖࢜ࣥࢆ㏻ࡍࣔࢹ
⣽⳦࡭ࢇẟ࣮ࣔࢱ࣮㸪ᅛᐃᏊ」ྜయ, ࢖࢜ࣥࢳࣕࢿࣝ, ࣓ࢳ࢜ࢽࣥ 13C ࣓ࢳࣝᇶᶆ㆑
‫࠺ࢁࡘࡓࡢࡁࡋ࡟ۑ‬㸪ࡇࡌࡲࡏ࠸ࡌ, ࡯ࢇࡲࡳࡕ࠾, ࡳࡸࡢ࠸ࡾࡼ࠺࡬࠸

－ 62 －

ࣝࡀᥦ᱌ࡉࢀࡓ (2,3) ࠋࡇࡢࣔࢹࣝࢆド᫂ࡍࡿࡓࡵ࡟ᡃࠎ
ࡶ V. alginolyticus ࡢᅛᐃᏊ」ྜయࡢᵓ㐀ࢆࢡࣛ࢖࢜㟁Ꮚ㢧ᚤ㙾ࢆ⏝࠸ࡓ༢⢏Ꮚゎᯒἲ࡛᫂ࡽ࠿࡟ࡍࡿࡇ࡜࡟ࡋࡓࠋࡑ
ࡢ⤖ᯝࠊ V. alginolyticus ࡢᅛᐃᏊ」ྜయࡶ 5 ศᏊࡢ PomA
࡜ 2 ศᏊࡢ PomB ࠿ࡽᡂࡿࡇ࡜ࡀࢃ࠿ࡗࡓ (Fig. 2) ࠋH+㥑ືᆺࡢ MotAB 」ྜయ࡛ࡣ H+ 㓄఩఩⨨ࡢྠᐃࡀᅔ㞴ࡔࡀࠊ Na+ 㥑ືᆺࡢ PomAB 」ྜయ࡛ࡣ Na+ ࡢ᳨ฟࡀྍ⬟࡛స⏝ṧᇶࡢྠᐃࡀᮇᚅࡉࢀࡓࠋࡋ࠿ࡋ࡞ࡀࡽࠊ༢⢏Ꮚゎᯒἲ࡛ᚓࡽࢀࡓ࣐ࢵࣉ࡜ࣔࢹࣝᵓ㐀࠿ࡽࡣṇ☜࡞Na+ ࡢ㓄఩఩⨨ࡀ≉ᐃ࡛ࡁ࡞࠿ࡗࡓࠋࡑࡇ࡛ࠊ⁐ᾮ᰾☢Ẽඹ㬆ἲ (NMR) ࢆ⏝࠸࡚ᅛᐃᏊ」ྜయࢆゎᯒࡍࡿࡇ࡜࡛ࠊ Na+ ࡢ⤖ྜ࡟ࡼࡾ⏕ࡌࡿᵓ㐀ኚ໬ࢆ᫂ࡽ࠿
࡟ࡋࡓ࠸࡜⪃࠼ࡓࠋᅛᐃᏊ」ྜయࡣ⣙ 200 kDa ࡢศᏊ㔞ࢆᣢࡕࠊLB ᇵᆅ 1 L ࠶ࡓࡾ࠿ࡽ 1 mg (~5 M)ࡢ᭱⤊⢭〇ࢧࣥࣉࣝࢆㄪ〇ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡇࡢศ
Ꮚ㔞࡜཰㔞࠿ࡽ୍⯡ⓗ࡞ࢧࣥࣉࣝㄪ〇ἲ࡜ ᐃἲ࡛ࡣゎᯒࡀᅔ㞴࡛࠶ࡿࡇ࡜ࡀண᝿ࡉࢀࡓࡓࡵࠊ」ྜయ୰ࡢ
࣓ࢳ࢜ࢽࣥṧᇶࡢ࣓ࢳࣝᇶࢆ ≉␗ⓗ࡟ 13C ᶆ㆑ࡋࡓࢧࣥࣉࣝࢆㄪ〇ࡋࠊࡑࡢࢫ࡮ࢡࢺࣝࢆ ᐃࡍࡿࡇ࡜࡟
ࡋࡓ (Fig. 3) ࠋPomA ཬࡧ PomB ࡟ࡣࡑࢀࡒࢀ 17,
16 ṧᇶࡢ࣓ࢳ࢜ࢽࣥࡀᏑᅾࡍࡿࠋNa+ ࡢ⤖ྜ࡟౫Ꮡࡋࡓᵓ㐀ኚ໬ࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵ࡟ࠊ㔝⏕ᆺ (WT)
ᅛᐃᏊ」ྜయࡢヨᩱ࡟ Na+ ࢆྵࡴヨᩱ࡜ྵࡲ࡞࠸ヨᩱࢆㄪ〇ࡋࠊᚓࡽࢀࡓ 2 ḟඖ 1H-13C
HMQC ࢫ࣌ࢡࢺࣿࢆẚ㍑ࡋࡓࠋࡲࡓࠊࡇࢀࡲ࡛ࡢኚ␗యゎᯒ࠿ࡽ PomB ࡢ⭷㈏㏻㡿ᇦ࡟Ꮡᅾࡍ
ࡿᚲ㡲ࡢ࢔ࢫࣃࣛࢠࣥ㓟ṧᇶ (D24) ࡟ Na+ ࡀ⤖ྜࡍࡿࡇ࡜ࡀศ࠿ࡗ࡚࠾ࡾࠊࡇࡢṧᇶࡢ㟁Ⲵࢆ୰࿴ࡋࡓ D24N ኚ␗యࡣ Na+ ࡀ⤖ྜ࡛ࡁࡎࠊ࡭ࢇẟ࣮ࣔࢱ࣮ࡀᅇ㌿ࡋ࡞ࡃ࡞ࡿࡇ࡜ࡀศ࠿ࡗ࡚
࠸ࡿࠋࡑࡇ࡛ D24N ኚ␗ࢆᣢࡘヨᩱࢆㄪ〇ࡋࠊྠᵝ࡟ ᐃࢆ⾜ࡗࡓ࡜ࡇࢁࠊWT ࡢࢫ࣌ࢡࢺࣝ
࡜ẚ㍑ࡋ࡚໬Ꮫࢩࣇࢺኚ໬ࡢぢࡽࢀࡿಙྕࡀᏑᅾࡋࡓࠋᚓࡽࢀࡓࢫ࣌ࢡࢺࣝ୰ࡢಙྕࡢᖐᒓࢆ⾜࠺ࡓࡵࠊ PomA, PomB ࡢ⭷㈏㏻㡿ᇦࡢ࣓ࢳ࢜ࢽࣥṧᇶࢆࣟ࢖ࢩࣥࡲࡓࡣ࢖ࢯࣟ࢖ࢩࣥ࡟⨨᥮ࡋࡓኚ␗యヨᩱࢆㄪ〇ࡋࠊ ᐃࢆ⾜ࡗࡓࠋⓎ⾲࡛ࡣࠊࢡࣛ࢖࢜㟁㢧༢⢏Ꮚゎᯒ࡛ᚓࡽࢀࡓᵓ㐀᝟ሗ࡜ྜࢃࡏ࡚ Na+ ࡢ⤖ྜ࡟ࡼࡾ⏕ࡌࡿ V. alginolyticus ᅛᐃᏊ」ྜయࡢᵓ㐀ኚ໬࡟ࡘ࠸࡚㆟ㄽࡍࡿࠋ
References(1) Michio Homma, Seiji Kojima, Tatsuro Nishikino. (2022) Achievements in bacterial flagellar research withfocus on Vibrio species. Microbiol Immunol., 66, 75-95.
(2) Mònica Santiveri, Aritz Roa-Eguiara, Caroline Kühne, Navish Wadhwa, Haidai Hu, Howard C Berg, Marc
Erhardt, Nicholas M I Taylor. (2020) Structure and Function of Stator Units of the Bacterial Flagellar
Motor. Cell. 183, 244–257.
(3) Justin C Deme, Steven Johnson, Owen Vickery, Amy Aron, Holly Monkhouse, Thomas Griffiths, Rory
Hennell James, Ben C Berks, James W Coulton, Phillip J Stansfeld, Susan M Lea. Structures of the stator
complex that drives rotation of the bacterial flagellum. (2020) Nat Microbiol., 12, 1553-1564.

－ 63 －

L2-4

࢖ࣥࣂ࣮ࢫᆺᣑᩓࣉ࣮ࣟࣈࢆ⏝࠸ࡓྜᡂ㧗ศᏊࡢDOSY
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‫ྑۑ‬ᡭᾈ୍ 㸪Ώ㑔୍ஓ 㸪㧗ᯇி♸ 㸪Ώ㑔 㣁 㸪ᚨ⏣つ⣫ 
1 ᚨᓥ኱Ꮫ࣭኱Ꮫ㝔⌮ᕤᏛ◊✲⛉2 KURITA EUROPE࣭GmbH R&D department

DOSY measurements of synthetic polymers using an inverse geometry diffusion probe‫ۑ‬Koichi Ute1, Kazuya Watanabe1,2, Kyosuke Takamatsu1, Soh Watanabe1, Norihiro Tokuda1
1

Department of Applied Chemistry, Tokushima University

2

R&D department, KURITA EUROPE GmbHThe diffusion coefficient of macromolecules in solution is small. A “diffusion NMR probe system” thatcan generate a large pulsed field gradient (PFG) is advantageous for the measurement. However, this system
has been mainly used for nucleus with low gyromagnetic ratio (such as 7Li and 23Na) and thus is notnecessarily optimized for measurement of 1H nuclei. In this study, 1H diffusion-ordered two-dimensional
NMR (DOSY) experiments were carried out for synthetic polymers with average molecular weights
exceeding 1,000,000 in solution using an inverse geometry diffusion probe (maximum PFG intensity of 1700G/cm). The results for acrylamide-based polymer electrolytes and standard polystyrenepoly(methyl
methacrylate) systems are described.
⁐ᾮ୰࡟࠾ࡅࡿ㧗ศᏊࡢ⮬ᕫᣑᩓಀᩘ㸦D㸧
ࡣᑠࡉ࠸ࠋࡑࡢ

ᐃ࡟ࡣ኱ࡁ࡞ࣃࣝࢫ☢ሙ໙㓄

㸦PFG㸧ࢆⓎ⏕࡛ࡁࡿࠕᣑᩓࣉ࣮ࣟࣈࢩࢫࢸ࣒ࠖ
ࡀ᭷฼࡛࠶ࡿࡀ㸪ᚑ᮶㸪ࡇࡢࢩࢫࢸ࣒ࡣ୺࡜ࡋ
࡚ 7Li ࡸ 23Na ࡢࡼ࠺࡞ప☢Ẽᅇ㌿ẚ᰾ࡢᣑᩓᐃ࡟⏝࠸ࡽࢀ࡚ࡁࡓࡓࡵ㸪1H ᰾ࡢᐃ࡟ࡣᚲࡎࡋࡶ᭱㐺໬ࡉࢀ࡚࠸࡞࠸ࠋᮏ◊✲࡛ࡣ㸪1

H ᰾ࡢ

Fig.1  ThebppͲsteͲledsequence[1].ᐃ࡟㐺ࡋࡓ࢖ࣥࣂ࣮ࢫᆺᣑᩓࣉ࣮ࣟࣈ㸦᭱኱PFGᙉᗘ

1700 G/cm㸧ࢆ⏝࠸࡚㸪㔜㔞ᖹᆒศᏊ㔞㸦Mw㸧100୓ࢆ㉸࠼ࡿྜᡂ㧗ศᏊࡢDiffusion-ordered two-dimensional NMR㸦DOSY㸧 ᐃࢆ⾜ࡗࡓࠋ࢔ࢡࣜࣝ࢔࣑ࢻ⣔㧗ศᏊ㟁ゎ㉁㸪࡞ࡽࡧ࡟㸪ᶆ‽࣏ࣜࢫࢳࣞࣥ㸦PS㸧࣭࣏࣓ࣜࢱࢡࣜࣝ㓟࣓ࢳࣝ㸦PMMA㸧ΰྜ⣔ࡢ᳨ウ⤖ᯝ࡟ࡘ࠸࡚㏙࡭ࡿࠋ
DOSYᐃࡣ㸪5 mm Diff BBI probeࢆ⿦╔ࡋࡓBruker AvanceNEO 400ᆺNMR⿦⨨ࢆ⏝࠸㸪bpp-ste-ledࣃࣝࢫ⣔ิ㸦ᅗ1㸧࡟ࡼࡾ⾜ࡗࡓࠋࢹ࣮ࢱゎᯒ࡟ࡣTopSpin 4.1.4㸦Bruker㸧ࡢCONTINἲ㸪ࡲࡓࡣ㸪NMRnotebook 2.8 with DOSY module 2.7㸦NMRtec㸧ࡢ᭱኱

Fig.2  Structureofacrylamide(AAm)Ͳ[2Ͳ(acryloyloxy)Ͳ
ethyl]trimethylammonium
chloride(AETAC)copolymer.࢚ࣥࢺࣟࣆ࣮㸦MEM㸧ἲࢆ⏝࠸ࡓࠋ࢝ࢳ࢜ࣥᛶ࢔ࢡࣜࣝ࢔࣑ࢻ⣔ඹ㔜ྜయ㸦ᅗ2㸧㸦Mw = 3.9 u 106, Mw/Mn = 3.1, AETAC/AAm =࢔ࢡࣜࣝ࢔࣑ࢻ⣔㧗ศᏊ㟁ゎ㉁㸪ᶆ‽࣏ࣜࢫࢳࣞࣥ㸪࣏࣓ࣜࢱࢡࣜࣝ㓟࣓ࢳࣝ‫ࡕ࠸࠺ࡇ࡚࠺ۑ‬㸪ࢃࡓ࡞࡭࠿ࡎࡸ㸪ࡓ࠿ࡲࡘࡁࡻ࠺ࡍࡅ㸪ࢃࡓ࡞࡭ࡑ࠺㸪࡜ࡃࡔࡢࡾࡦࢁ

－ 64 －

81.3/18.7㸧࡜࣏ࣜ࢔ࢡࣜࣝ࢔࣑ࢻ㸦Mw = 1.3 u 106,
Mw/Mn = 1.6㸧ࡢ➼㔞ΰྜ≀ࢆNaCl㸦1 M㸧ࢆྵࡴ㔜Ỉ࡟0.2 wt%⁐ゎࡋࡓヨᩱࡢDOSYࢫ࣌ࢡࢺࣝࢆᅗ

4
3

§

5

1
2

3࡟♧ࡍࠋ኱ࡁ࡞PFGࢆ౑ࡗ࡚ᣑᩓ᫬㛫'ࢆ10 ms࡜▷⦰࡛ࡁࡓࡇ࡜࡛㸪ᶓ⦆࿴᫬㛫T2ࡢ▷࠸AETAC༢఩ࡢCH2ᇶ࡟ࡼࡿඹ㬆⥺㸦3࠾ࡼࡧ4㸧ࡸ୺㙐CHᇶ
࡟ࡼࡿඹ㬆⥺㸦2㸧ࡀ᫂░࡟ほࡉࢀࡿ࡜࡜ࡶ࡟㸪Mwࡢ␗࡞ࡿ2ࡘࡢ࣏࣐࣮ࣜᡂศࡢDࡢศᕸࡀศ㞳
ࡋ࡚ほ

ࡉࢀࡓࠋ

ᶆ‽PMMA 3✀㸦Mw = 1,840, 67,400, 1,677,000㸧࡜ྜࡋ࡚2 % w/v o-C6D4Cl2⁐ᾮ࡜ࡋ㸪60 °C࡛

ᐃࡋࡓ

DOSYࢫ࣌ࢡࢺࣝࢆᅗ4࡟♧ࡍࠋPMMAࡢOCH3ᇶ࡟
3ࡘ࡟ࡼࡃศ㞳ࡉࢀ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡿࠋOCH3ᇶ࡟ࡼࡿࣆ࣮ࢡ࡜㸪PSࡢC6H5ᇶ࡟ࡼࡿࣆ࣮ࢡࡀࡑࢀࡒࢀ

ORJŧ P V ᶆ‽PS 3✀㸦Mw = 2,800, 43,900, 1,260,000㸧ࢆ➼㔞ΰࡼࡿ3ࡘࡢࣆ࣮ࢡ࡜C6H5ᇶ࡟ࡼࡿ3ࡘࡢࣆ࣮ࢡ࠿ࡽࡑ
ࢀࡒࢀDࡢ್ࢆㄞࡳྲྀࡾ㸪ᑐᛂࡍࡿM್࡜୧ᑐᩘࣉࣟ
ࢵࢺࡋࡓ࡜ࡇࢁⰋዲ࡞┤⥺㛵ಀࡀᚓࡽࢀࡓ㸦ᅗ1ྑ㸧ࠋ
PMMA࡟ࡘ࠸࡚ࡣ D

0.643㸪PS࡟ࡘ࠸࡚ࡣ D

0.655࡛࠶ࡗࡓࠋࡇࡢࡼ࠺࡞ෆ㒊ᶆ‽ἲ࡟ࡼࡿከศ
ᩓPMMAࡢMw࡜Mw/Mnࡢᐃ⤖ᯝ࡟ࡘ࠸࡚ࡣㅮ₇ᙜ

᪥࡟㏙࡭ࡿࠋ
[1] D. Wu, A. Chen, C. S. Johnson, Jr., J. Magn. Reson.
Ser. A, 115, 260 (1995)

Fig.3  DOSYcontourplotsforamixtureofpolyacrylamide(Mw=1.3u106)andAAmͲ
AETACcopolymer(Mw=3.9u106)in1M
NaCl/D2O(0.2wt%)at30qC('10ms,G3.4ms,
Wg0.5Ps,64linearGgradientsteps,G120G/cm,
G641000G/cm,128scanswereaccumulatedper
eachGstep(totaltime11h23min).

Fig.4  DOSYcontourplotsforamixtureof3standardPMMAsamples(Mw1,840,67,400,1,677,000)and3
standardPSsamples(Mw2,800,43,900,1,260,000)inoͲC6D4Cl2(2%w/v)at60°CusingthebppͲsteͲled
pulsesequence.TheDOSYdatawasanalyzedbythemaximumentropymethod(MEM).RelevantDOSY
parametersareasfollows:'12ms,G4.0ms,Wg0.5Ps,128linearQgradientsteps(G120G/cm,G1281700
G/cm),64scanswereaccumulatedpereachGstep(totaltime11h23min).RelationshipbetweenMandD
obtainedbytheDOSYͲMEManalysisofthemixture.ThedataforPMMAandPSweredeterminedfromthe
resonancesofthemethoxyandphenylgroups,respectively.

－ 65 －

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L2-7

Paip2A inhibits translation by competitively binding to the RNA
recognition motifs of poly(A)-binding protein C1 and promoting its
dissociation from the poly(A) tailᐮἙỤ᙭ὶ㸪ᶓᕝ┿᲍Ꮚ㸪ἑᓮ⥤୍㸪▼஭⿱୍㑻㸪⣽⏣┤㸪ᫍ㔝┿୍㸪௒஭㥴㍜㸪ᔱ⏣୍ኵ㸪‫ۑ‬኱⃝໷⠊
1៞᠕⩏ሿ኱኱Ꮫ㝔࣭⸆Ꮫ◊✲⛉, 2ྡྂᒇᕷ❧኱኱Ꮫ㝔࣭⸆Ꮫ◊✲⛉, 3ᮾி኱኱Ꮫ㝔࣭⸆Ꮫ⣔◊✲⛉, 4⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮

Takeru Sagae1, Mariko Yokogawa1, Ryoichi Sawazaki1, Yuichiro Ishii1, Nao Hosoda2, Shin-ichi Hoshino2,
Shunsuke Imai3,4, Ichio Shimada3,4, ‫ۑ‬Masanori Osawa1
1

Graduate School of Pharmaceutical Sciences, Keio University, 2Graduate School of Pharmaceutical

Sciences, Nagoya City University, 3Graduate School of Pharmaceutical Sciences, The University of Tokyo,
4Center for Biosystems Dynamics Research, RIKEN

Eukaryotic mRNAs possess a poly(A) tail at their 3'-end, to which poly(A)-binding protein C1 (PABPC1)
binds and recruits other proteins that regulate translation. PABP-interacting protein 2A (Paip2A) effectively
inhibits poly(A)-dependent translation by causing the dissociation of PABPC1 from the poly(A) tail; however,the underlying mechanism remains unknown. This study was conducted to investigate the functional
mechanisms of Paip2A action by characterizing the PABPC1–poly(A) and PABPC1–Paip2A interactions by
ITC and NMR. Based on the results, we propose the functional mechanism for Paip2A: Paip2A initially binds
to the RRM2 region of poly(A)-bound PABPC1, and RRM2-anchored Paip2A effectively displaces the
RRM3 region from poly(A), resulting in dissociation of the whole PABPC1 molecule.
┿᰾⏕≀ࡢ᰾ෆ࡛ྜᡂࡉࢀࡓmRNAࡣࠊ5 ‫ޗ‬ᮎ➃࡟capࡀࠊ3‫ޗ‬ᮎ➃࡟poly(A)ࡀ௜ຍࡉࢀࡓᚋࠊ⣽⬊㉁࡟㍺㏦ࡉࢀࡿࠋPoly(A)࡟ࡣPoly(A)⤖ྜࢱࣥࣃࢡ㉁㸦PABPC1㸧ࡀ⤖ྜࡋࠊPABPC1ࡣᵝࠎ࡞⩻ヂᅉᏊ࡜┦஫స⏝ࡍࡿࡇ࡜࡛⩻ヂࢆㄪ⠇ࡍࡿࠋ
PABP-interacting protein 2 A (Paip2A) ࡣPABPC1ࢆpoly(A)࠿ࡽゎ㞳ࡉࡏࡿࡇ࡜࡛⩻ヂࢆᢚไࡍࡿࠋ
Paip2Aࡣࡀࢇ໬ࡋࡓNIH3T3⣽⬊ࡢቑṪࢆᢚไࡍࡿࡇ࡜ࡸࠊࢹࣥࢢ࢘࢖ࣝࢫࡢቑṪࢆᢚไࡍࡿࡇ࡜
ࡀሗ࿌ࡉࢀ࡚࠸ࡿࠋࡑࡢࡓࡵࠊPaip2A࡟ࡼࡿPABPC1ࡢゎ㞳ࡢศᏊ࣓࢝ࢽࢬ࣒ࢆゎ᫂ࡍࡿࡇ࡜࡟ࡼ
ࡾࠊ᪂ࡓ࡞ᢠࡀࢇ๣࣭ᢠ࢘࢖ࣝࢫ⸆ࡢ㛤Ⓨ࡟⧅ࡀࡿࡇ࡜ࡀᮇᚅ࡛ࡁࡿࠋPABPC1ࡣ636ṧᇶ࠿ࡽ࡞ࡿࢱࣥࣃࢡ㉁࡛࠶ࡾࠊNᮎ➃ഃ࡟ࡣࢱࣥࢹ࣒࡟୪ࡪ4ࡘࡢRNAㄆ㆑ࣔࢳ࣮ࣇ(RRM) ࢆࠊCᮎ➃ഃ࡟ࡣPABC࡜࿧ࡤࢀࡿࢻ࣓࢖ࣥࢆᣢࡕࠊࡑࡢ㛫ࡣ⣙170ṧᇶࡢlinker࡟ࡼࡾ⧅ ࡀ ࢀ ࡚ ࠸ ࡿ(Fig. 1) ࠋ

RRM1/2/3/4ࡣpoly(A)࡜⤖ྜࡋࠊࡑࡢゎ㞳ᐃᩘ (Kd) ࡣ0.15 nM࡜ࠊ
PABPC1 ඲ 㛗 ࡢ poly(A) ࡜ ࡢ ⤖ ྜ
ࡢKd (0.69 nM)࡜࡯ࡰྠ➼࡛࠶ࡾࠊ
RRM1/2/3/4ࡀpoly(A)⤖ྜ࡟୺せFig. 1. Domain structures of PABPC1 and Paip2A࡞ᙺ๭ࢆᯝࡓࡋ࡚࠸ࡿࠋ
poly(A)-binding protein, Paip2A, functional mechanismࡉࡀ࠼ࡓࡅࡿ㸪ࡼࡇࡀࢃࡲࡾࡇ㸪ࡉࢃࡊࡁࡾࡻ࠺࠸ࡕ㸪࠸ࡋ࠸ࡺ࠺࠸ࡕࢁ࠺㸪࡯ࡑࡔ࡞࠾㸪࡯ࡋࡢࡋࢇ࠸ࡕ㸪࠸ࡲ࠸ࡋࡹࢇࡍࡅ㸪ࡋࡲࡔ࠸ࡕ࠾㸪‫ࡾࡢࡉࡲࢃࡉ࠾࠾ۑ‬－ 70 －

Paip2Aࡣ127ṧᇶ࠿ࡽ࡞ࡿࢱࣥࣃࢡ㉁࡛࠶ࡾࠊNᮎ➃ഃ࡟ࡣRRM࡜⤖ྜࡍࡿPABP-interacting motif
1 (PAM1) ࢆࠊCᮎ➃ഃ࡟ࡣPABC࡜⤖ྜࡍࡿPABP-interacting motif 2 (PAM2) ࢆᣢࡘ (Fig. 1)ࠋPAM1
࡜RRM1/2/3/4࡜ࡢ⤖ྜࡢKdࡣ0.66 nMࠊPAM2࡜PABCࡢ⤖ྜࡢKdࡣ74௅400 nM࡛࠶ࡾࠊPAM1ࡢ᪉ࡀPABP࡜ࡢ⤖ྜぶ࿴ᛶࡀⴭࡋࡃ㧗࠸ࠋ௨ୖࡢࡇ࡜࠿ࡽࠊPaip2AࡢPAM1࡜RRM࡜ࡢ┦஫స⏝ࡀࠊPaip2A࡟ࡼࡿpoly(A)࠿ࡽࡢPABPC1ࡢゎ㞳࡟୺せ࡞ᙺ๭ࢆᯝࡓࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿࠋࡋ࠿ࡋ࡞ࡀࡽࠊPABPC1ࡢpoly(A)࠾ࡼࡧ
Paip2A࡬ࡢ⤖ྜぶ࿴ᛶࡣ࡝ࡕࡽࡶ⣙0.7 nM࡜࡯ࡰྠ➼࡛࠶ࡿ࡟ࡶ࠿࠿ࢃࡽࡎࠊ࡝ࡢࡼ࠺࡟Paip2A
ࡀຠ⋡ⓗ࡟PABPC1ࢆpoly(A)࠿ࡽゎ㞳ࡉࡏࡿ࠿ࡢᶵᵓࡣ୙࡛᫂࠶ࡿࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊPABPC1
࡜poly(A)ࠊ࠾ࡼࡧࠊPaip2A࡜PABPC1࡜ࡢ┦஫స⏝ࢆゎᯒࡍࡿࡇ࡜࡛ࠊPaip2࡟ࡼࡿpoly(A)࠿ࡽࡢ
PABPゎ㞳ࡢ࣓࢝ࢽࢬ࣒ࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋࡓࠋPaip2AୖୖࡢRRM1/2/3/4⤖⤖ྜ㡿ᇦࡢྠᐃ
[13C, 15N] Paip2Aࢆ⏝࠸ࡓ୺㙐㐃㙐ᖐᒓࢆ⾜࠸ ࠊ ᘬ ࡁ ⥆ ࡁ [2H, 15N] Paip2A ࡟ ᑐ ࡋ ࡚
RRM1/2/3/4ࢆ⁲ᐃࡋࡓ࡜ࡇࢁࠊPaip2Aࡢṧᇶ
␒ྕ26௅83␒ࡢ 1H-15N TROSYࢩࢢࢼࣝࡀᾘኻ
ࡋࡓࠋࡇࡢࡇ࡜࠿ࡽࠊࡇࡢ㡿ᇦࢆRRM1/2/3/4⤖
ྜ㡿ᇦ࡜ྠᐃࡋࡓࠋ௨㝆ࡢゎᯒ࡛ࡣࠊPaip2A(25-83)ࡢ㡿ᇦࢆ⏝࠸ࡓࠋ

Fig. 2 CSPs of Paip2A upon binding to
RRM1/2/3/4

⁲ᐃ࣓࢝ࣟࣜࢺ࣮ࣜ (ITC) ࡟ࡼࡿྛRRM࡟
࡟ᑐࡍࡿpoly(A)࠾
࠾ࡼࡧPaip2Aࡢ
ࡢ⤖ྜぶ࿴ᛶゎᯒ

➼

ITC ࡟࡚ࠊA7 ࡜ྛ RRM ࡢ┦஫స⏝ゎᯒࢆ⾜ࡗࡓ⤖ᯝࠊRRM1 ࠾ࡼࡧ RRM4 ࡣ A7
࡜ࡢ⤖ྜ࡟ࡼࡿ⇕㔞ኚ໬ࡣほࡉࢀ࡞࠿ࡗࡓ (Table 1)ࠋ୍᪉࡛ࠊRRM2 ࠾ࡼࡧ
RRM3 ࡣ A7 ࡜ࡢ⤖ྜ࡟ࡼࡿ⇕㔞ኚ໬ࡀほࡉࢀࠊA7 ࡟ᑐࡍࡿ RRM2 ࠾ࡼࡧ RRM3
ࡢ⤖ྜࡢ Kd ࡣࠊࡑࢀࡒࢀ 200 ȝM ࡜ 4.7 ȝM

Table 1 Kd values for the A7-RRM interaction
RRM

N*

Kd (M)

RRM1

N.D.

N.D.

RRM2

1.4 ± 0.1

(2.0 ± 0.4) × 10-4

RRM3

1.2

(4.7 ± 0.3) × 10-6

RRM4

N.D.

N.D.

*N : Molar ratio of RRM against A7࡛࠶ࡾࠊࢫࢺ࢖࣓࢟࢜ࢺ࣮ࣜࡣ࡝ࡕࡽࡶ
1:1 ࡛࠶ࡗࡓ (Table 1)ࠋ
ࡲࡓࠊPaip2A(25-83)࡜ྛ RRM ࡢ┦஫స⏝ゎᯒࢆ⾜ࡗࡓ⤖ᯝࠊRRM1 ࠾ࡼࡧ RRM4
ࡣ Paip2A(25-83)࡜ࡢ⤖ྜ࡟ࡼࡿ⇕㔞ኚ໬ࡣほࡉࢀ࡞࠿ࡗࡓ (Table 2)ࠋ୍᪉࡛ࠊRRM2

࠾ࡼࡧ RRM3 ࡣ Paip2A(25-83)࡜ࡢ⤖ྜ࡟ࡼࡿ⇕㔞ኚ໬ࡀほࡉࢀࠊPaip2A(25-83)࡟ᑐ

ࡍࡿ RRM2 ࠾ࡼࡧ RRM3 ࡢ⤖ྜࡢ Kd ࡣࠊࡑࢀࡒࢀࠊ4.0 ȝM ࠾ࡼࡧ 1.3 ȝM ࡛࠶ࡾࠊࢫ
ࢺ࢖࣓࢟࢜ࢺ࣮ࣜࡣ࡝ࡕࡽࡶ 1:1 ࡛࠶ࡗࡓ

Table 2 Kd values for the Paip2A(25-83)-RRM
interaction
RRM

N*

Kd (M)

RRM1

N.D.

N.D.

RRM2

0.87 ± 0.03

(4.0 ± 0.5) × 10-6

RRM3

0.87

(1.3 ± 0.1) × 10-6

RRM4
N.D.
N.D.
*N : Molar ratio of RRM against Paip2A(25-83)(Table 2)ࠋ

－ 71 －NMR࡟࡟ࡼࡿRRM2/3ୖ
ୖࡢ࡜poly(A)⤖⤖ྜ㒊఩ࡢྠᐃ

Poly(A)࡜ࡢ⤖ྜ࡟㛵୚ࡍࡿ RRM2/3 ࡢṧᇶࢆྠᐃࡍࡿࡓࡵࠊ[13C, 15N] RRM2/3 ࠾ࡼࡧ[13C, 15N] RRM2/3A12 」ྜయࡢ 1H-15N HSQC ᐃࠊ࠾ࡼࡧࠊྛ✀୕㔜ඹ㬆 ᐃࢆ⾜࠸ࠊ୺㙐ࢩࢢࢼࣝࢆᖐᒓࡋࡓࠋࡉࡽ࡟ࠊA12ࡢῧຍ࡟క࠺ RRM2/3 ࡢࢩࢢࢼࣝࡢኚ໬ࢆゎᯒࡋࠊA12ࡢῧຍ࡟ࡼࡾ኱ࡁ࡞໬Ꮫࢩࣇࢺኚ໬ࡀぢࡽࢀࡓࢩࢢ
ࢼࣝ࡟ᑐᛂࡍࡿṧᇶࢆ RRM2 ࠾ࡼࡧ RRM3 ࡢᵓ㐀ୖ࡟࣐ࢵࣆࣥࢢࡋࡓࠋࡑࡢ⤖ᯝࠊࡑࢀࡽࡢṧᇶࡣࠊ
RRM2/3 ࡢྛ RRM ࡢ ȕ ࢩ࣮ࢺഃ࡟ᒁᅾࡋ࡚࠸ࡓ (Fig.
3a, b ⥳Ⰽࡢṧᇶ)ࠋࡇࡢࡇ࡜ࡣࠊRRM2/3 ࡢྛ RRM ࡢȕ ࢩ࣮ࢺഃ࡟ poly(A)ࡀ⤖ྜࡍࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋ

Fig. 3 Mapping of the affected
residues of (a) RRM2 and (b) RRM3
in RRM2/3 upon binding to A12

NMR࡟࡟ࡼࡿRRM2/3࡜
࡜Paip2Aࡢ
ࡢ┦஫స⏝ゎᯒPaip2A ࡜ࡢ⤖ྜ࡟㛵୚ࡍࡿ RRM2/3 ࡢṧᇶࢆྠᐃࡍࡿࡓࡵࠊ[13C, 15N] RRM2/3 ࠾ࡼࡧ[13C, 15N] RRM2/3Paip2A(25-83)」ྜయࡢ 1H-15N HSQC ᐃࠊ࠾ࡼࡧࠊ
ྛ✀୕㔜ඹ㬆 ᐃࢆ⾜࠸ࠊ1H-15N HSQC ࢫ࣌ࢡࢺࣝୖ࡟ほ ࡉࢀࡓ୺㙐࢔࣑ࢻࢩࢢࢼࣝࢆᖐᒓࡋࡓࠋࡉࡽ
࡟ࠊPaip2A(25-83)ῧຍ࡟క࠺ RRM2/3 ࡢࢩࢢࢼࣝࡢ
ኚ໬ࢆゎᯒࡋࠊPaip2A(25-83)ࡢῧຍ࡟ࡼࡾ኱ࡁ࡞໬
Ꮫࢩࣇࢺኚ໬ࡀぢࡽࢀࡓࢩࢢࢼࣝ࡟ᑐᛂࡍࡿṧᇶࢆ
RRM2 ࠾ࡼࡧ RRM3 ࡢᵓ㐀ୖ࡟࣐ࢵࣆࣥࢢࡋࡓࠋࡑ
ࡢ⤖ᯝࠊࡑࢀࡽࡢṧᇶࡣࠊRRM2/3 ࡢྛ RRM ࡢ ȕ ࢩ࣮ࢺഃ࡟ᒁᅾࡋ࡚࠸ࡓ (Fig. 4a, b ࣐ࢮࣥࢱࡢṧᇶ)ࠋ
ࡇࡢࡇ࡜ࡣࠊRRM2/3 ࡢྛ RRM ࡢ ȕ ࢩ࣮ࢺഃࠊࡍ࡞
ࢃࡕࠊRRM2/3 ࡢ poly(A)⤖ྜ㒊఩࡟ Paip2A(25-83)ࡀ
⤖ྜࡍࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋ

Fig. 4 Mapping of the affected residuesof (a) RRM2 and (b) RRM3 in RRM2/3
upon binding to Paip2A(25-83)

NMR ࡟ࡼࡿ Paip2A(25-83)࡜
࡜ RRM2/3, RRM2, RRM3 ࡢ┦஫స⏝ゎᯒḟ࡟ࠊ[2H, 13C, 15N] Paip2A(25-83)࡟ᑐࡍࡿ RRM2/3 ࡢ NMR ⁲ᐃᐇ㦂ࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊ
Paip2A(25-83)ࡢ࢔࣑ࣀ㓟ṧᇶ␒ྕ 31௅79 ␒ࡢ㡿ᇦ࡟ࠊ0.1 ppm ࢆ㉸࠼ࡿ኱ࡁ࡞໬Ꮫࢩࣇࢺኚ໬ࡀぢࡽࢀࡓ (Fig. 5)ࠋࡇࡢࡇ࡜ࡣࠊPaip2A(25-83)ࡢ࢔࣑ࣀ㓟ṧᇶ␒ྕ 31௅79 ␒ࡢ㡿ᇦࡀ RRM2/3
࡜ࡢ┦஫స⏝࡟㛵୚ࡍࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿ ࠋ
ࡉࡽ࡟ࠊPaip2(25-83)ࡢ N ᮎ➃ࡢ31௅44 ␒ࡢṧᇶࡢࢩࢢࢼࣝࡀࠊ㧗☢ሙ࠾ࡼࡧప☢ሙഃ࡟ศᩓࡋ࡚ほ ࡉࢀ
ࡓ (Fig. 6)ࠋࡇࡢṧᇶࡀ RRM2 ࡜
RRM3 ࡢ࡝ࡕࡽ࡜┦஫స⏝ࡋࡓ࠿ࢆㄪ࡭ࡿࡓࡵࠊ[15N] Paip2A(25-83)࡟ᑐ
ࡍࡿ RRM2 ࠾ࡼࡧ RRM3 ࡢ NMR ⁲ᐃᐇ㦂ࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊRRM2 ῧ Fig. 5㻌 Affected residues of Paip2A(25-83) upon binding
to RRM2/3
ຍ᫬ࡢࢫ࣌ࢡࢺ࡛ࣝࡣࠊศᩓࡋࡓࢩ

－ 72 －

ࢢࢼࣝࡣぢࡽࢀ࡞࠿ࡗࡓ
(Fig. 6a)ࠋ୍᪉࡛ࠊRRM3 ῧຍ᫬ࡢࢫ࣌ࢡࢺ࡛ࣝࡣࠊRRM2/3
ῧຍ᫬ࡢࢫ࣌ࢡࢺࣝୖ࡟ほࡉࢀࡓ Paip2A(25-83)ࡢ N ᮎ➃ഃࡢṧᇶ࡟⏤᮶ࡍࡿࢩࢢࢼࣝ
࡜࡯ࡰྠࡌ఩⨨࡟ࠊศᩓࡋࡓࢩ ࢢ ࢼ ࣝ ࡀ ぢ ࡽ ࢀ ࡓ (Fig.
6b)ࠋࡇࡢࡇ࡜ࡣࠊPaip2A(2583)ࡢ N ᮎ➃ഃࡢ㡿ᇦࡀ RRM3
࡜┦஫స⏝ࡍࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋ

Fig. 6 㻌 Spectral overlay of HSQC of Paip2A(25-83) in thepresence of (a) RRM2 and (b) RRM3 over HSQC in the presenceof RRM2/3࠙⪃ᐹࠚᮏ◊✲ࡼࡾࠊpoly(A)࡜ Paip2A ࡟ᑐࡍࡿ RRM2 ࡢ⤖ྜࡢ Kd ࡣࡑࢀࡒࢀ 200 ȝM ࠾ࡼࡧ 4.0
ȝM ࡛࠶ࡾࠊpoly(A)࡟ᑐࡍࡿ⤖ྜぶ࿴ᛶ࡟ẚ࡭ࠊPaip2A ࡟ᑐࡍࡿ⤖ྜぶ࿴ᛶࡀ 50 ಸ኱ࡁ࠸ࡇ
࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓࠋࡇࡢࡇ࡜࠿ࡽࠊPaip2A ࡣ poly(A)ࡼࡾඃඛⓗ࡟ RRM2 ࡟⤖ྜྍ⬟࡛࠶ࡿ࡜⪃࠼ࡓࠋࡲࡓࠊPaip2A(25-83)ࡣࠊpoly(A)࡜ྠᵝ࡟ࠊRRM2/3 ࡢ ȕ ࢩ࣮ࢺഃ࡟⤖ྜࡋࡓࠋࡇ
ࡢࡇ࡜࠿ࡽࠊPaip2A ࡣ PABPC1 ࡢ RRM ࡜ poly(A)࡜ࡢ⤖ྜࢆ➇ྜⓗ࡟㜼ᐖࡍࡿ࡜⪃࠼ࡓࠋ௨ୖࡢ⤖ᯝ࠿ࡽࠊPaip2 ࡟ࡼࡿ poly(A)࠿ࡽࡢ PABP ゎ㞳ࡢ࣓࢝ࢽࢬ࣒࡟ࡘ࠸࡚ࠊḟࡢࣔࢹࣝࢆᥦၐࡋࡓࠋࡲࡎࠊPABPC1 ࡣ 4 ࡘࡢ RRM ࡢ୰࡛ࡶ≉࡟ poly(A)࡟ᑐࡋ࡚ぶ࿴ᛶࡢ㧗࠸ RRM2
࠾ࡼࡧ RRM3 ࢆ୺࡜ࡋ࡚ poly(A)࡟⤖ྜࡍࡿ (Fig. 7a)ࠋࡑࡇ࡟ Paip2A ࡀᏑᅾࡍࡿ࡜ࠊPaip2A
ࡣ RRM2 ࡟ᑐࡍࡿ⤖ྜぶ࿴ᛶࡀ poly(A)ࡼࡾ㧗࠸ࡓࡵࠊpoly(A)ࡼࡾࡶඃඛⓗ࡟ RRM2 ࡟⤖ྜ
ࡋࠊRRM2 ࡢ poly(A)࡬ࡢ⤖ྜࢆ➇ྜⓗ࡟㜼ᐖࡍࡿ(Fig. 7b)ࠋࡉࡽ࡟ࠊPaip2A ࡣ RRM2 ࡟ࢸࢨࣜࣥࢢࡉࢀࡿࡇ࡜࡛ RRM3 ࡢ poly(A)⤖ྜ㒊఩ࢆຠ⋡ⓗ࡟㜼ᐖࡍࡿࡇ࡜ࡀ࡛ࡁࡿ(Fig. 7b)ࠋࡑ
ࢀ࡟ࡼࡾࠊPABPC1 ࡀ poly(A)࠿ࡽゎ㞳ࡍࡿࠋ

Fig. 7 Proposed model of the dissociation of PABPC1 from poly(A) by Paip2A(a) RRM2 and RRM3 of PABPC1mainly contribute to the poly(A) binding. (b) Paip2A accesses
RRM2 of PABPC1, whose affinity for poly(A) is 50-fold lower than that for Paip2A. Once Paip2A
is tethered to RRM2, the local concentration of the adjacent RRM3 binding region of Paip2A
increases around RRM3, leading to the effective binding of Paip2A to RRM3 competitively againstpoly(A).

Reference
Sagae T, Yokogawa M, Sawazaki R, Ishii Y, Hosoda N, Hoshino S, Imai S, Shimada I, Osawa M. (2022)
Paip2A inhibits translation by competitively binding to the RNA recognition motifs of PABPC1 and promoting
its dissociation from the poly(A) tail. J. Biol. Chem. 298 (5) 101844.

－ 73 －

L2-8࢔ࢹࣀࢩࣥA2Aཷᐜయ࡜ࣜ࢞ࣥࢻࡢ⁫ᅾ᫬㛫ࢆつᐃࡍࡿᵓ㐀ᇶ┙ࡢゎ᫂‫ ⏣ୖۑ‬༟ぢࠊᅵ⏣ ▱㍤ࠊᰩ⏣ ᨻ⛱ࠊỈᮧ ᣅஓࠊ௒஭ 㥴㍜ࠊⓑ▼ ຬኴ㑻ࠊᖾ⚟ ⿱ࠊ➉ෆ ᜏࠊᔱ⏣ ୍ኵ
1ᮾி኱Ꮫ኱Ꮫ㝔࣭⸆Ꮫ⣔◊✲⛉2⌮໬Ꮫ◊✲ᡤ⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮

Structural basis of the residence time of adenosine A2A receptor and the ligands‫ۑ‬Takumi Ueda1, Tomoki Tsuchida1, Masatoshi Kurita1, Takuya Mizumura1, Shunsuke Imai1,2, Yutaro
Shiraishi1,2, Yutaka Kofuku1, Koh Takeuchi1, Ichio Shimada1,2
1 Graduate School of Pharmaceutical Sciences, The University of Tokyo
2 RIKEN Center for Biosystems Dynamics Research

Residence time of a drug and its receptor is a key parameter of the pharmacological drug actions.
Adenosine A2A receptor and the ligands reportedly exhibit various residence times. However, themechanism underlying the multi-level residence time remains elusive. Here, we observed NMR signals of
alanine and methionine methyl groups in the ligand-binding site of adenosine A2A receptor and its mutants
with reduced residence times. Our NMR analyses revealed that spatial arrangement of the E165-H264
salt bridge correlates with the residence time. These finding provide quantitative insight into theresidence time and will be helpful for development of drugs with desirable pharmacological actions.
⸆≀ࡀཷᐜయศᏊ࡟⁫ᅾࡍࡿ᫬㛫ࡣࠊ⸆≀ࡢຠᯝ࡟┤⤖ࡍࡿࠋ⾑⟶ᣑᙇࡸ⅖⑕཯ᛂไᚚࠊ㐠ືࢆྖࡿ⚄⤒ఏ㐩࡟㛵୚ࡍࡿGPCR࡛࠶ࡿ࢔ࢹࣀࢩࣥA2Aཷᐜయ (A2AAR) ࡛ࡣࠊᚰ➽࢖࣓࣮ࢪࣥࢢ
ࡢ⸆≀࡜ࡋ࡚ࡣ⁫ᅾ᫬㛫ࡀ▷࠸᪉ࡀ๪స⏝ࢆ㜵ࡄୖ࡛ᮃࡲࡋ࠸୍᪉ࠊࣃ࣮࢟ࣥࢯࣥ⑓ࡸ⅖⑕࡟ᑐࡍࡿ⸆࡜ࡋ࡚ࡣ⁫ᅾ᫬㛫ࡀ㛗࠸᪉ࡀ᭷ຠᛶࡀᣢ⥆ࡍࡿⅬ࡛ᮃࡲࡋ࠸ࠋA2AAR࡛ࡣࠊ⁫ᅾ᫬㛫ࡀẚ
㍑ⓗ㛗࠸ZM241385ࡸẚ㍑ⓗ▷࠸LUF5834➼ࡢ⁫ᅾ᫬㛫ࡢ␗࡞ࡿࣜ࢞ࣥࢻࡢᏑᅾࡀ▱ࡽࢀ࡚࠸ࡿ
2AARࡢ

⤖ᬗᵓ㐀࡛ࡣࠊࣜ࢞ࣥࢻ⤖ྜ࣏ࢣࢵࢺࡢୖ㒊࡟
E169࡜H264ࡀሷᶫࢆᙧᡂࡋ࡚࠾ࡾࠊE169࠾ࡼࡧ
H264࡟㏆᥋ࡍࡿT256࡬ࡢኚ␗ᑟධ࡟ࡼࡾ⁫ᅾ᫬㛫ࡀపୗࡍࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿ1 (Fig.1)ࠋࡋ࠿

A

NECA

LUF5834(LUF)

ࡋࠊ⁫ᅾ᫬㛫ࡀẚ㍑ⓗ▷࠸≧ែ࡟࠾ࡅࡿࣜ࢞ࣥࢻ
⤖ྜᵝᘧࡀᮍ▱࡛࠶ࡿࡓࡵࠊ⁫ᅾ᫬㛫ࢆỴᐃࡍࡿᶵᵓࡣ୙࡛᫂࠶ࡿࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊࣜ࢞ࣥࢻ
ࡢ⁫ᅾ᫬㛫ࡀᵝࠎ࡟␗࡞ࡿ᮲௳࡟࠾࠸࡚ࠊA2AAR
ࡢࣜ࢞ࣥࢻ⤖ྜ㒊఩ࡢᵓ㐀ࢆゎᯒࡋ࡚ࠊ⁫ᅾ᫬㛫ࢆỴᐃࡍࡿᶵᵓࢆゎ᫂ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋࡓࠋB

ZM241385(ZM)
Long RT(~1 min)

Short RT
(×1/8,
1~10 s)100

Residence time of
ZM241385(min)1,2 (Fig.1)ࠋࡲࡓࠊZM241385⤖ྜ≧ែࡢA

10

1

WT E169Q T256A
1/60 1/17(~1 min) (1~10 sec)

Fig. 1. Residence time of A2AAR and ligands.
A. chemical structures and residence time (RT)of A2AAR ligands1,2. B. Effect of mutations on
the residence time of A2AAR and ZM2413851.

GPCR㸪⭷ࢱࣥࣃࢡ㉁, ᪻⹸⣽⬊Ⓨ⌧⣔‫ࡳࡃࡓࡔ࠼࠺ۑ‬㸪ࡘࡕࡔ࡜ࡶࡁ㸪ࡃࡾࡓࡲࡉ࡜ࡋ, ࡳࡎࡴࡽࡓࡃࡸ, ࠸ࡲ࠸ࡋࡹࢇࡍࡅ, ࡋࡽ࠸ࡋࡺ࠺ࡓࢁ࠺, ࡇ࠺ࡩࡃࡺࡓ࠿, ࡓࡅ࠺ࡕࡇ࠺, ࡋࡲࡔ࠸ࡕ࠾

－ 74 －

᪻⹸⣽⬊Ⓨ⌧⣔ࢆ⏝࠸࡚ࠊ࣓ࢳ࢜ࢽࣥṧᇶ࡜࢔ࣛࢽࣥṧᇶࡢ࣓ࢳࣝᇶࢆ㑅ᢥⓗ࡟ᶆ㆑ࡋࡓA2AAR
ࢆㄪ〇ࡋ࡚ࠊZM241385⤖ྜ≧ែࡢ1H-13C HMQCࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓࠋྛṧᇶࡢኚ␗యࡢࢫ࣌ࢡ
ࢺࣝ࡜ẚ㍑ࡍࡿࡇ࡜࡛ࠊࣜ࢞ࣥࢻ⤖ྜ㒊఩࡟఩⨨ࡍࡿṧᇶࡢNMRࢩࢢࢼࣝࢆᖐᒓࡍࡿࡇ࡜ࡀ࡛ࡁ

Fig. 2. Resonances from A2AAR in theࡓ (Fig.2)ࠋḟ࡟ࠊ⁫ᅾ᫬㛫ࡀ1/60⛬ᗘ࡟పୗࡍࡿ

ZM241385-bound state.

ࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࠊE169Qኚ␗యࡢࢫ࣌ࢡࢺࣝ

A. Alanine and methionine regions of the 1H-13C

ࢆྲྀᚓࡋࡓࠋࡑࡢ⤖ᯝࠊA265ࡢࢩࢢࢼࣝࡀ㢧ⴭ

HMQC spectra.

࡟1Hప☢ሙࢩࣇࢺࡋࡓ (Fig. 3A)ࠋ⤖ᬗᵓ㐀ୖ࡛

assigned methionine and alanine residues in theࡣࠊA265ࡢ1H໬ᏛࢩࣇࢺࡣH264࡟㏆᥋ࡋ࡚࠾ࡾࠊA265ࡢ1H໬ᏛࢩࣇࢺࡣH264ࡢ⎔㟁ὶࢩࣇࢺ

B. Distribution of thecrystal structure of A2AAR.

࡟ࡼࡾつᐃࡉࢀࡿ࡜⪃࠼ࡽࢀࡿࠋࡋࡓࡀࡗ࡚ࠊ
A265ࡢ1H໬ᏛࢩࣇࢺࡣE169-H264ࡢሷᶫࡢ≧ែࢆ཯ᫎࡍࡿࡇ࡜ࠊ࠾ࡼࡧE169Aኚ␗య࡛ࡣࡇࡢሷᶫ
ࡀᙧᡂࡉࢀ࡚࠸࡞࠸ࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
ḟ࡟ࠊ⁫ᅾ᫬㛫ࡀ1/17⛬ᗘ࡟పୗࡍࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࠊT256Aኚ␗యࡢࢫ࣌ࢡࢺࣝࢆྲྀᚓࡋ

Fig. 3. Overlaid A265 signals of A2AAR underࡓࠋࡑࡢ⤖ᯝࠊA265ࡢ1H໬Ꮫࢩࣇࢺࡣ㔝⏕ᆺ࡜the conditions with various residence times.

E169Aኚ␗యࡢ୰㛫ⓗ࡞್࡛࠶ࡗࡓ(Fig. 3B)ࠋࡲ

A.

ࡓࠊ⁫ᅾ᫬㛫ࡀZM241385ࡢ1/8⛬ᗘ࡛࠶ࡿࡇ࡜ࡀ

ZM241385-bound▱ࡽࢀ࡚࠸ࡿࠊLUF5834⤖ྜ≧ែ࡟࠾ࡅࡿࢫ࣌ࢡ

A2AAR/E169Q, and A2AAR/T256A in theࢺࣝ࡟࠾࠸࡚ࡶࠊA265ࡢ1H໬Ꮫࢩࣇࢺࡣ㔝⏕ᆺ

ZM241385-bound࡜E169Aኚ␗యࡢ୰㛫ⓗ࡞್࡛࠶ࡗࡓ(Fig. 3C)ࠋA2AAR/E169Q in the ZM241385-bound stateࡋࡓࡀࡗ࡚ࠊT256Aኚ␗య࠾ࡼࡧLUF5834⤖ྜ≧and A2AAR in the LUF5834-bound state.

A2AAR

and

A2AAR/E169Q

theB. A2AAR,

state.
state.

in

C.

A2AAR

and

ែ࡛ࡣࠊA265ࡢE169-H264ࡢሷᶫࡀ㒊ศⓗ࡟ኚㄪࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ(Fig. 4)ࠋࡲࡓࠊୖグࡢ≧ែ࡟࠾࠸࡚ࠊA265ࡢ1H໬Ꮫࢩࣇࢺ࡜ࣜ࢞ࣥ
ࢻࡢ⁫ᅾ᫬㛫ࡀⰋࡃ┦㛵ࡋࡓࡇ࡜࠿ࡽࠊE169࡜H264ࡢሷᶫࡢ≧ែࡀࠊ⁫ᅾ᫬㛫ࢆつᐃࡍࡿ࡜⪃࠼ࡓࠋ

Fig. 4. Schematic diagrams of the conformation of the ligand binding site of A2AAR.
References(1) Guo D, et al. (2016) Molecular basis of ligand dissociation from the adenosine A2A receptor. Mol. Pharmacol.
89, 485-91,(2) Guo D, et al. (2012) Functional efficacy of adenosine AၷA receptor agonists is positively correlated to their
receptor residence time. Br. J. Pharmacol. (2012) 166, 1846-59.

－ 75 －

ਸ਼2঩৯
11া9঩‫ق‬਷‫ك‬ஶୁ७ॵ३ঙথ

Day 2
Wednesday, 9th Nov.
English Sessions

L3-1

Mapping the per-residue surface electrostatic potential of
CAPRIN1 along its phase separation trajectory‫ۑ‬Yuki Toyama እᒣ ౡᶞ 1-3, Atul Kaushik Rangadurai1-4,
Julie D. Forman-Kay2, 4, and Lewis E. Kay1-4
1 Department of Molecular Genetics, University of Toronto
2 Department of Biochemistry, University of Toronto
3 Department of Chemistry, University of Toronto
4 Hospital for Sick Children, Program in Molecular Medicine

Mapping the per-residue surface electrostatic potential of CAPRIN1 along its phaseseparation trajectory‫ۑ‬Yuki Toyama1-3, Atul Kaushik Rangadurai1-4, Julie D. Forman-Kay2, 4, and Lewis E. Kay1-4
1

Department of Molecular Genetics, University of Toronto

2

Department of Biochemistry, University of Toronto

3

Department of Chemistry, University of Toronto

4

Hospital for Sick Children, Program in Molecular Medicine

The surface charges of biomolecules can significantly affect how they interact with each other, including, insome cases, whether they can undergo liquid-liquid phase separation. One example is the RNA binding
protein CAPRIN1, an important component in membraneless organelles involved in RNA processing.
Focusing on the C-terminal intrinsically disordered, positively charged region of CAPRIN1, we have mappedout at a residue specific level the role of electrostatics in phase separation promoted by the addition of ATP.
We show that the propensity of CAPRIN1 to form condensates is coupled to its neutralization and formationof intermolecular contacts. Our results highlight the interplay between repulsive electrostatic forces andfavorable inter-chain interactions in regulating the formation of CAPRIN1 condensates.

1. Introduction
CAPRIN1 is found in membraneless organelles such as stress granules, P bodies, and mRNAtransport granules, where it plays an important role in regulating RNA processing. The C-terminal region of
the CAPRIN1 has been shown to phase separate in vitro. The primary sequence of this C-terminal
intrinsically disordered, phase-separating region of CAPRIN1 (hereafter referred to as CAPRIN1) is divided
into N- and C-terminal Arg-rich regions, and a middle region that is depleted in arginines but rich in aromatic
residues (Fig. 1A). CAPRIN1 has 15 Arg residues, a pI of 11.5 and a charge of +13 at physiological pH. Not
surprisingly, therefore, phase separation requires the addition of salt to screen unfavorable electrostaticinteractions; alternatively, the phase separation of CAPRIN1 can be promoted by adding negatively charged
molecules such as ATP or RNA to a CAPRIN1 solution. Recent exciting advances in NMR spectroscopy
provide an avenue for the de novo experimental determination of near-surface electrostatic potentials (‫׋‬ENS)
in biomolecules with atomic resolution, and under a wide range of ionic strengths and solvent condition1.
With the availability of methods for measuring near-surface electrostatic potentials of proteins, here weestablished quantitatively the important role of electrostatics in controlling the phase separation of CAPRIN1,
by monitoring how ‫׋‬ENS “evolves” during the ATP-induced phase separation process.
Intrinsically disordered proteins, Biomolecular condensates, Paramagnetic relaxation enhancement－ 78 －

'HQRYRGHWHUPLQDWLRQRISHUUHVLGXHVXUIDFHHOHFWURVWDWLFSRWHQWLDOVRI&$35,1
Iwahara and co-workers have demonstarated thatsolution NMR spectroscopy can be used to measure ‫׋‬ENS at eachbackbone amide1. This is illustrated schematically in Fig. 1B, wheresolvent PREs from the positively or negatively charged 2,2,5,5tetramethylpyrrolidine-N-oxyl nitroxide (PROXYL) derivatives, 3aminomethyl-PROXYL and 3-carboxy-PROXYL, respectively, aremeasured. The measurement of PREs for a pair of differently
charged co-solutes provides an avenue for the determination of perresidue ‫׋‬ENS values, via the relation

where 2e is the charge difference between 3-aminomethyl- (+1e)
and 3-carboxy-PROXYL (−1e), kB is Boltzmann’s constant, T is theabsolute temperature, and Ȟଶǡ௜ ݅ ‫ א‬ሼ൅ǡ െሽ is the R2 PRE rate for agiven proton measured from either the + or – spin label. Using themeasured PRE rates, ‫׋‬ENS values were determined for individual
residues in CAPRIN1. Fig. 1C shows the resulting residue-specific‫׋‬ENS profile. Intriguingly, a positive potential of § +20 mV wasmeasured in the aromatic-rich regions of CAPRIN1, even though )LJ  $  6FKHPDWLF GLDJUDP RI &
the net charge in this central portion of the protein is small. The WHUPLQDOUHJLRQRI&$35,1 % 7KH
QHDUVXUIDFHHOHFWURVWDWLFSRWHQWLDORID
positive potential in the middle section of the protein likely reflects FKDUJHG SURWHLQ OHDGV WR GLVWLQFW
the slight imbalance in charge skewed towards positive as well as VROYHQW 35( SDWWHUQV IRU GLIIHUHQWO\FKDUJHG 352;</ GHULYDWLYHV & 
the dynamic nature of the CAPRIN1 whereby the N- and C-terminal 3ORWRI‫(׋‬16YDOXHVRI&$35,1 S+DQG& 
Arg-rich regions contact the central portion of the molecule.

$GGLWLRQRI$73UHGXFHVDQGXOWLPDWHO\LQYHUWVWKHHOHFWURVWDWLFSRWHQWLDORI&$35,1
Turbidity assays (Fig. 2A), measuring light scattering that accompanies phase separation, as afunction of ATP concentration established that addition of ATP to CAPRIN1 solutions promotes phaseseparation when concentrations of nucleotide in the approximate range of 1~ 60 mM are added, andsubsequent re-entry into a mixed state at higher concentrations of ATP (> 60 mM). 7KLVLVFRQVLVWHQWZLWKDQLPSRUWDQWUROHIRUHOHFWURVWDWLFVLQWKHSKDVHVHSDUDWLRQRI&$35,1E\$73 DQGRWKHUQHJDWLYHO\FKDUJHG
PROHFXOHVVXFKDV51$ DQGKDVPRWLYDWHGXVWRLQYHVWLJDWHKRZ‫(׋‬16YDOXHVFKDQJHXSRQWKHDGGLWLRQRI
$73We measured per-residue ‫׋‬ENS values for CAPRIN1 at a pair of ATP concentrations: 0.8 mM where
ATP initiates phase separation, with CAPRIN1 in a predominantly mixed state, and 90 mM where CAPRIN1
has re-entered the mixed state after phase separation (Fig. 2B). We observed a significant decrease in ‫׋‬ENS
by 10~30 mV upon the addition of 0.8 mM ATP (the values depending on the ATP/CAPRIN1 ratio), whileat 90 mM ATP the surface potential of CAPRIN1 had inverted, becoming negative.
1HXWUDOHOHFWURVWDWLFSRWHQWLDORIFRQGHQVHGSKDVHRI&$35,1
We were interested in establishing what the surface electrostatic potential is for CAPRIN1 in thecondensed phase of the demixed state, as the experiments recorded on the mixed state CAPRIN1 sample－ 79 －

suggest that, while ‫׋‬ENS must be small, values that are slightly positive, slightly negative, or completely
neutral would be possible. An ATP-induced demixed sample was prepared using a bulk concentration of 3
mM ATP, with two distinct liquid phases (Fig. 2C), including a CAPRIN1-depleted phase on top (dilutephase; 200 ȝM in protein, 2.5 mM ATP) and a CAPRIN1-concentrated phase on the bottom (condensed
phase; 51 mM in protein, 258 mM ATP). Since the bottom phase covers the radio frequency coil for NMR
signal detection, signals from the protein-condensed phase could be selectively observed, and the per-residue
electrostatic potential of the CAPRIN1 condensate could, therefore, be measured. Fig. 2C shows the 15N-1H
TROSY HSQC spectrum of CAPRIN1 in the condensed phase recorded using a sample containing 2% 2H,
15

N-labeled protein in an unlabeled CAPRIN1 background (pH 5.5 and 40 °C). Deuteration leads tosignificant gains in both spectral sensitivity and resolution. The solvent PREs were very similar between thepositive and negative PROXYL derivatives across the protein and the surface potential of CAPRIN1 in thecondensed phase was close to neutral across the protein (Fig. 2D). Thus, charge neutralization is a prerequisite
for forming a stable CAPRIN1 condensed phase.

Fig. 2 (A) Turbidity assays measuring phase separation propensities of CAPRIN1 as a function of [ATP].
(B) Plots of ‫׋‬ENS values measured with 0 mM, 0.8 mM (with two different CAPRIN1 concentrations), and90 mM ATP. (C) 15N-1H TROSY HSQC spectrum of a condensed phase CAPRIN1 sample (258 ± 11 mM
ATP and 50.6 ± 1.9 mM protein). The NMR sample tube containing the demixed state sample is shown. (D)
CAPRIN1 ‫׋‬ENS potentials in the condensed phase.
5. Correspondence between reduced electrostatic potential and intermolecular interactions
We hypothesized that intermolecular contacts between CAPRIN1 chains would concomitantly
strengthen along the trajectory towards phase separation by the addition of ATP, as the electrostic potentialof CAPRIN1 decreases, leading to less electrostatic repulsion between proximal molecules. To characterizeintermolecular interactions between CAPRIN1 chains, we performed an intermolecular PRE experiment inwhich a spin-label (TEMPO) was covalently attached to one half of the molecules (not isotopically labeled)
and the effects on the spectra of 13C, 15N-labeled molecules in the sample quantified (Fig. 3A). The
measurements were also performed in the presence of 0.8 mM ATP, where CAPRIN1 starts to phase separate,
and at 90 mM ATP, where the ‫׋‬ENS distribution is slightly negative (Fig. 2B).
In the absence of ATP, no significant intermolecular PREs were observed, consistent withcontacts between CAPRIN1 chains being largely suppressed by electrostatic repulsion between thepositively-charged molecules (Fig. 3B). In contrast, in the presence of 0.8 mM and 90 mM ATP, significant
intermolecular PREs are observed. Notably, the intermolecular PREs, and hence intermolecular contacts, arelargest in the presence of 90 mM ATP where the surface electrostatic potential is closest to neutral along the－ 80 －

backbone of the protein (−3.4 mV, on average) and decrease as the surface charge increases (maximum ‫׋‬ENS
values of +40 mV and + 30 mV for samples with 0 mM and 0.8 mM ATP, respectively) (Fig. 3B). The
observed PREs from A658C-TEMPO were larger in the aromatic-rich portions of the molecule, consistent
with our previous intermolecular NOE analyses showing a number of interaction hotspots (residues 624-626,
638-640, and 660-666) localized to these aromatic-rich regions2.
5. Discussions
Our results establish that, at least in thepositively charged CAPRIN1 system, decreases in‫׋‬ENS upon addition of increasing amounts of ATP
correlate with progression towards the phase-separated
state, as illustrated schematically in Fig. 3C. In theabsence of ATP, CAPRIN1 has a positive surface
potential across the molecule (>+20 mV), withmaxima at the N- and C-terminal Arg-rich regions of
the protein (ൎ+40mV). Thus, electrostatic repulsion ofproximal chains prevents self-association (Fig. 3C,
step I). Upon addition of ATP, the positive surface
potential of CAPRIN1 decreases, initially more in
Arg-rich regions, showing that ATP interacts initiallywith the positively charged termini of the protein (Fig.
5, step II). Increasing amounts of ATP eventually leadto accumulation of a condensed phase (demixed state)
and neutralization of CAPRIN1 chains (Fig. 3C, step
III), where each protein molecule interacts withapproximately 5 equivalents of ATP. Neutralization of
CAPRIN1 is accompanied by favorable intermolecular)LJ  $  6FKHPDWLF RI WKH VDPSOH FRPSRVLWLRQ
XVHGWRPHDVXUHWKHLQWHUPROHFXODU35(HIIHFW % ,QWHUPROHFXODU 35( SURILOH IURP$&7(032
RI &$35,1 &  7KH JUDSKLFDO VXPPDU\ RI WKH
UROHRIHOHFWURVWDWLFSRWHQWLDOVLQUHJXODWLQJSKDVHVHSDUDWLRQRI&$35,1

interactions connecting neighboring CAPRIN1 molecules, stabilizing the protein-condensed phase (Fig. 3C,
step III). Our intermolecular PRE results show a strong correlation between reduction in electrostatic
potential and enhanced intermolecular interactions, supporting the model. Further addition of ATP (> 60mM) leads to re-entrance into a mixed phase. This is accompanied by a charge inversion of CAPRIN1, witha slight negative potential localized to the aromatic-rich regions of the molecule. The net negative potentialof the CAPRIN1 chain likely prevents the intermolecular interactions that are required for phase separation,
leading to disassembly of condensates (Fig. 3C, step IV). Thus, electrostatics play a central role in modulating
the biological functions of this protein, and measurement of electrostatic potentials at each site along its
backbone provides an opportunity to understand in more detail the important role of charge in this system.
References(1) B. Yu, C. C. Pletka, B. M. Pettitt, J. Iwahara, De novo determination of near-surface electrostatic potentials
by NMR. Proc. Natl. Acad. Sci. USA 118, e2104020118 (2021).
(2) T. H. Kim, et al., Interaction hot spots for phase separation revealed by NMR studies of a CAPRIN1
condensed phase. Proc. Natl. Acad. Sci. USA 118, e2104897118 (2021).

－ 81 －

L3-2

GPCR࡜ࡢ┦஫స⏝࡟ࡼࡿ ȕ-࢔ࣞࢫࢳࣥ1ࡢ2ẁ㝵άᛶ໬żⓑ▼ຬኴ㑻1㸪ᖾ⚟⿱2㸪ୖ⏣༟ぢ2㸪Shubhi Pandey3㸪Hemlata DwivediAgnihotri3㸪Arun K. Shukla3㸪ᔱ⏣୍ኵ11⌮໬Ꮫ◊✲ᡤ⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮2ᮾி኱Ꮫ኱Ꮫ㝔⸆Ꮫ⣔◊✲⛉3࢖ࣥࢻᕤ⛉኱Ꮫ࢝ࣥࣉ࣮ࣝᰯ

Biphasic activation of ȕ-arrestin 1 upon interaction with a GPCR revealed by methylTROSY NMR
ɧYutaro Shiraishi1, Yutaka Kofuku2, Takumi Ueda2, Shubhi Pandey3, Hemlata Dwivedi-Agnihotri3, Arun K.
Shukla3, Ichio Shimada1
1

Laboratory for Dynamic Structure of Biomolecules, RIKEN Center for Biosystems Dynamics Research(BDR), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
2

Graduate School of Pharmaceutical Sciences, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo

113-0033, Japan3

Department of Biological Sciences and Bioengineering, Indian Institute of Technology, Kanpur 208016,

India
ȕ-arrestins (ȕarrs) play multifaceted roles in the function of G protein-coupled receptors (GPCRs).
ȕarrs typically interact with phosphorylated C-terminal tail (C tail) and transmembrane core (TM core) of
GPCRs. However, the effects of the C tail- and TM core-mediated interactions on the conformational
activation of ȕarrs have remained elusive. Here, we show the conformational changes for ȕarr activation
upon the C tail- and TM core-mediated interactions with a prototypical GPCR by nuclear magnetic
resonance (NMR) spectroscopy. Our NMR analyses demonstrated that while the C tail-mediatedinteraction alone induces partial activation, in which ȕarr exists in equilibrium between basal and activatedconformations, the TM core- and the C tail-mediated interactions together completely shift the equilibrium
toward the activated conformation. This plasticity of ȕarr conformation in complex with GPCRs engaged
in different binding modes may explain the multifunctionality of ȕarrs.
ȕ-࢔ࣞࢫࢳࣥ (ȕarr) ࡣࠊࣜ࢞ࣥࢻࡀ⤖ྜࡋࠊ࠿ࡘࣜࣥ㓟໬ࢆཷࡅࡓGࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయ
(GPCR) ࡟⤖ྜࡍࡿࡇ࡜࡛ࠊGࢱࣥࣃࢡ㉁౫Ꮡⓗ࡞ࢩࢢࢼࣝఏ㐩ࢆ⤊஢ࡉࡏࡿ࡜࡜ࡶ࡟ࠊGࢱࣥࣃࢡ㉁㠀౫Ꮡⓗ࡞ࢩࢢࢼࣝఏ㐩ࢆㄏ㉳ࡍࡿࠋȕarrࢆ௓ࡋࡓࢩࢢࢼࣝఏ㐩ࡣࠊGࢱࣥࣃࢡ㉁ࢆ௓ࡋ
ࡓࢩࢢࢼࣝఏ㐩࡜ࡣ␗࡞ࡿ⏕⌮ᛂ⟅ࢆไᚚࡋ࡚࠾ࡾࠊȕarrࡢάᛶ໬ᶵᵓࡢ⌮ゎࡣGPCRࢆᶆⓗ࡜ࡋࡓ๰⸆㛤Ⓨ࡟㈉⊩ࡍࡿࠋࡇࢀࡲ࡛࡟ᡃࠎࡣࠊGPCR࢟ࢼ࣮ࢮ࡟ࡼࡾࣜࣥ㓟໬ࡉࢀࡓGPCRࡢCᮎ➃㡿ᇦ (C tail) ࡀࠊ⭷㈏㏻ࢻ࣓࢖ࣥ (TM core) ࡜┦஫స⏝ࡍࡿࡇ࡜࡛ࡑࡢᵓ㐀ࢆኚ໬ࡉࡏࠊȕarr࡜ࡢ⤖ྜ࡟㐺ࡋࡓᵓ㐀ࢆ࡜ࡿࡇ࡜ࢆ♧ࡋࡓ1ࠋࡋ࠿ࡋ࡞ࡀࡽࠊTM coreࡸC tail࡜ȕarrࡢ┦஫స⏝ࡀࠊȕarrࡢᵓ㐀ࢆ࡝ࡢࡼ࠺࡟ኚ໬ࡉࡏ࡚࠸ࡿ࠿ࡣ୙࡛᫂࠶ࡿࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊGPCRࡢTM
core࡜C tailࡀࠊࡑࢀࡒࢀȕarrࡢᵓ㐀ࢆ࡝ࡢࡼ࠺࡟ኚ໬ࡉࡏࡿ࠿ࢆゎ᫂ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋ࡚ࠊ
NMR࡟ࡼࡿᵓ㐀ゎᯒࢆ⾜ࡗࡓࠋGࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయ㸪࢔ࣞࢫࢳࣥ
‫࠺ࢁࡓ࠺ࡺࡋ࠸ࡽࡋۑ‬㸪ࡇ࠺ࡩࡃࡺࡓ࠿㸪࠺࠼ࡔࡓࡃࡳ㸪ࡋࡹࡧ࠷ࡥࢇ࡛࠷㸪࡬ࡴࡽࡓ࡛࠷࡭࡛
࠷㸪࠶ࡿࢇࡋࡹࡃࡽ㸪ࡋࡲࡔ࠸ࡕ࠾

－ 82 －

ᮏ◊✲࡛ࡣࠊȕarr࡜ࡢ⤖ྜࡀቑᙉࡋࡓȕ2࢔ࢻࣞࢼࣜࣥཷᐜయࡢኚ␗
య (ȕ2V2R) ࢆゎᯒ࡟⏝࠸ࡓࠋࡲࡎࠊ
TM coreࡢάᛶ໬ࠊC tailࡢࣜࣥ㓟໬ࡀȕarr1ࡢ⤖ྜぶ࿴ᛶࢆ࡝ࡢࡼ࠺࡟
ኚ໬ࡉࡏࡿ࠿ࢆ⾲㠃ࣉࣛࢬࣔࣥඹ
㬆ἲ࡟ࡼࡾゎᯒࡋࡓࠋࡑࡢ⤖ᯝࠊC
tailࡀࣜࣥ㓟໬ࡉࢀ࡚࠸࡞࠸ȕ2V2R
࡜ȕarr1ࡢ≉␗ⓗ࡞⤖ྜࡣ᳨ฟࡉࢀ
࡞࠿ࡗࡓ୍᪉࡛ࠊC tailࡀࣜࣥ㓟໬ࡉࢀࡓȕ2V2Rࡣࠊȕarr1࡜ゎ㞳ᐃᩘ

Figure 1 | Chemical shift difference between basal andactivated state and mapping of the residues with chemical
shift differences

Kd = 0.2 ȝM࡛⤖ྜࡍࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋࡲࡓࠊC tailࡀࣜࣥ㓟໬ࡉࢀࡓȕ2V2R࡜ȕarr1ࡢぶ࿴ᛶࡣࠊࣜ࢞ࣥࢻ࡟ࡼࡿ
TM coreࡢάᛶ໬࡟ࡼࡾቑᙉࡍࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋḟ࡟ࠊȕ2V2RࡢC tailࠊTM core࡜ࡢ┦஫స⏝࡟ࡼࡾȕarr1࡟࡝ࡢࡼ࠺࡞ᵓ㐀ኚ໬ࡀ⏕ࡌࡿ࠿ࢆ⁐ᾮNMRἲ࡟ࡼࡾゎᯒࡋࡓࠋ[u-2H, Ileį1-13C1H3] ȕarr1ࢆㄪ〇ࡋࠊ୙άᛶᆺ࡟ᑐ
ᛂࡍࡿ༢⊂≧ែࠊάᛶ໬ᆺ࡟ᑐᛂࡍࡿసື⸆⤖ྜᆺࣜࣥ㓟໬ȕ2V2R (P-R*) ⤖ྜ≧ែࡢ1H-13C HMQCࢫ࣌ࢡࢺࣝࢆ
ẚ㍑ࡋࡓ࡜ࡇࢁࠊ୺࡟ȕarr1ࡢNࢻ࣓࢖ࣥ࡜Cࢻ࣓࢖ࣥࡢ⏺
㠃࡟ศᕸࡍࡿI31ࠊI168ࠊI207ࠊI214ࠊL241ࠊI314ࠊI317ࠊ
I386 ࡟ 0.1 ppm௨ ୖ ࡢ㢧ⴭ ࡞ ໬ Ꮫ ࢩ ࣇࢺ ᕪ ࢆ ᳨ฟ ࡋ ࡓ(Fig. 1)ࠋࡇࡢ⤖ᯝࡣࠊȕarr1ࡢάᛶ໬࡟క࠸2ࡘࡢࢻ࣓࢖ࣥ
ࡢ┦ᑐ㓄⨨ࡀኚ໬ࡍࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋC tail࡜ࡢ⤖ྜ
Figure 2 | (Top) Resonances from㏫సື⸆⤖ྜᆺࣜࣥ㓟໬ȕ2V2R (P-R) ⤖ྜ≧ែȕarr1ࡢ H- I207 in basal state, the complex withphosphorylated ȕ2V2R bound to the
13C HMQCࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓࠋࡑࡢ⤖ᯝࠊάᛶᆺࡢࢩ
full agonist, and the complex withࢢࢼࣝࢆ♧ࡋࡓṧᇶࡣI158ࠊI241ࠊI317ࡢࡳ࡛࠶ࡾࠊI31ࠊ phosphorylated ȕ2V2R bound to theI105ࠊI207ࠊI233ࠊI386ࡣ୙άᛶᆺ࣭άᛶᆺ࡟ᑐᛂࡍࡿࢩ inverse agonist(Bottom) Schematic representation ofࢢࢼࣝࡀ᳨ฟࡉࢀࡓ (Fig. 2, Top)ࠋ௨ୖࡢ⤖ᯝࡣࠊC tail the conformational activation of ȕarr1ࡢࡳ࡜⤖ྜࡋࡓ≧ែࡣ୙άᛶᆺ࡜άᛶᆺࢆ஺᥮ࡋ࡚࠾ upon binding to the phosphorylated
GPCRs
ࡾࠊάᛶᆺࡢᏑᅾẚࡀప࠸ࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ
ࡢࡳ࡛ȕarr1ࡢᵓ㐀ኚ໬ࡀㄏ㉳ࡉࢀࡿ࠿ࢆㄪ࡭ࡿࡓࡵ࡟ࠊ
1௨ୖࡢ⤖ᯝ࠿ࡽࠊGPCR࡟ࡼࡿȕarr1ࡢάᛶ໬ࡀࠊࡲࡎGPCR C tail࡜ࡢᙉ࠸⤖ྜ࡟ࡼࡾ」ྜయᙧ
ᡂࢆ㛤ጞࡋࠊ⥆࠸࡚㉳ࡇࡿTM core࡜ࡢᙅ࠸┦஫స⏝ࡀศᏊ඲యࡢᵓ㐀ኚ໬ࢆㄏ㉳ࡍࡿࠊ࡜࠸࠺2ẁ㝵ࡢືⓗ࡞㐣⛬࡛࠶ࡿࡇ࡜ࢆᥦၐࡍࡿ2 (Fig. 2, Bottom)ࠋ
References(1) Phosphorylation-induced conformation of ȕ2-adrenoceptor related to arrestin recruitment revealed by
NMR. Shiraishi Y, Natsume M, Kofuku Y, Imai S, Nakata K, Mizukoshi T, Ueda T, Iwaï H, Shimada I.
Nat. Commun. (2018) 9:194.
(2) Biphasic activation of ȕ-arrestin 1 upon interaction with a GPCR revealed by methyl-TROSY NMR.
Shiraishi Y, Kofuku Y, Ueda T, Pandey S, Dwivedi-Agnihotri H, Shukla AK, Shimada I. Nat. Commun.
(2021) 12:7158.

－ 83 －

An affinity-driven protonation-coupled substrate transport of a
MATE transporter

L3-3

Koh Takeuchi1 and Ichio Shimada1,2Graduate School of Pharmaceutical Sciences, University of Tokyo, Tokyo, Japan

RIKEN Center for Biosystems Dynamics Research, Yokohama, Japan.

The multidrug resistance (MDR) systems are ubiquitous in life, as the extrusion of cytotoxic compounds
is essential for maintaining cellular homeostasis and survival. The MDR activities are often achieved by asystem consisting of polyspecific multidrug-binding transcriptional factors and multidrug-efflux transporters,
in which increased expression of multidrug-efflux transporters is achieved by binding a range of toxic
compounds to multidrug-binding transcriptional factors. Elevated expression of multidrug-efflux transporters
in pathogens and cancers constitutes a significant challenge for medication, as it reduces the effects ofantibiotics and chemotherapeutic compounds etc.
The multidrug and toxin extrusion (MATE) family is a monomeric 12-transmembrane (TM) multidrugefflux transporters. Structures of MATE
transporters share a unique topology
where two lobes of 6-TM bundles(hereafter, we call the TM1-6 and TM712

bundles

respectively)

as

N-

form

and

C-lobe,pseudo-dimeric

structures that face each other about themembrane normal (Fig. 1). N- and Clobes

areconnected

by

a

long

intracellular loop (IL6-7, Fig. 1 bottom

Fig. 1 PfMATE structures in the OF and IF conformations.

right in each structure).
Compound efflux is coupled with H+ influx in Pyrococcus furiosus MATE (PfMATE). Thus, thetransporter is classified as H+-coupled antiporters. Most of the MATE structures were solved in the outwardfacing (OF) conformations, in which the two lobes interact tightly at the intracellular side forming a large
cavity open toward the extracellular/periplasmic side (Fig. 1, left). Especially, the tight mainchain interaction
between two conserved Gly residues (Gly96 and Gly309) at the intracellular closing, called the Gly gate, is
proposed to stabilize the OF conformation.
Similar to other transporter families, the MATE transporters are considered to transport ligands by analternating access mechanism, in which a ligand export is coupled with a whole-molecular isomerization
between the OF conformation (Fig. 1, left) and the inward-facing (IF) conformation (Fig. 1, right). However,the structural mechanisms of the conformational rearrangements have not been fully elucidated, as only one
IF conformation has been reported thus far, and the partially unfolded TM1 conformation observed in thereported IF crystal structure has been criticized as it seems to reflect the packing interactions imposed by
crystal contacts between protomers. Thus, the whole structural landscape of the proton-coupled compoundtransport mechanism of the MATE transporter at a functional condition is not yet conducted. In addition,
while some protonation sites that are important for transport activity, such as Asp41 and Glu163, were
proposed, the roles of these residues in the proton-coupled substrate antiport are not structurally elucidated.
Dynamics, Transporter, Conformational Equilibriums－ 84 －

To address these central issues of the transport mechanism, we carried out
the structural and dynamical analyses of PfMATE solubilized in n-dodecyl-ȕD-maltoside (DDM) micelle under different pH conditions by using nuclear
magnetic resonance (NMR) spectroscopy. All NMR data were corrected atelevated temperature (50°C), which is more relevant to the protein from athermophilic bacterium and substantially higher than currently available
structural studies.
From the pH-dependent chemical shift change (Fig. 2) and the solvent
accessibility deduced from the PRE experiments (Fig. 3), NMR analyses
revealed that PfMATE resides predominantly in the OF conformations at
neutral pH (pH 6.8) while mostly in the IF conformation at acidic pH (pH 3.7).
In the intermediate pH range, PfMATE is under a slow conformational
equilibrium between the OF and IF conformations (Fig. 2, middle). In line withthese notions, mutation of the glycine gate (Gly86 and Gly309) or the
intracellular protonation site (Glu163) shifts the conformational equilibrium
toward the IF conformation by disrupting the key interactions that stabilize the
OF conformation. In contrast, the disruption of the extracellular protonation
site, Asp41, did not alter the conformational equilibrium between the OF/IF
conformations. Thus, we concluded that the protonation of Glu163 is criticallyimportant for the conformational switch between the OF and IF conformations.
We also found that the binding of substrates, ethidium, is stronger to the IF

Fig. 2 NMR spectrum ofconformation (~40 ȝM) than that to the OF conformation (> 1 mM). The same

PfMATE at distinct pH

was valid for another substrate, norfloxacin. From this observation, we propose

conditions.

an affinity-driven export of compounds by
PfMATE. Even though the substrates canbind both N- and C-robe sides of cavities,
they bind only weakly to the OF
conformation.

Thus,

the

compounds

dissociate easily from PfMATE in the OF
conformation at the last step of thetransporting process.
In contrast, the high-affinity compoundinteraction to the IF conformation biases thesubstrate interaction occurs mostly on theintracellular side, in an occasion when
Glu163 is protonated. and the successive
proton release from Glu163 induces theFig. 3 Solvent PRE experiments of PfMATE at (A) neutral

spontaneous switch from the IF to OF

and (B) acidic conditions.

conformations. Since Glu163 is in theintracellular side and the presence of the positively charged compounds blocks the proton migration to the
OF cavity, the proton release should happen toward the intracellular side. This would explain the couplingof the substrate export and the proton import in the transporter. Thus, our NMR data provide unique evidence
to propose that PfMATE export substrates via an affinity-driven proton-coupled antiport mechanism.

－ 85 －

L3-4

Correlation and distance measurements between 1H and 14N using 14N
overtone NMR spectroscopy‫ۑ‬Yusuke Nishiyama1,2
1

JEOL RESONANCE Inc.

2

RIKEN-JEOL Collaboration Center, RIKEN

Inspired by the pioneering work of direct observation of14

N overtone transitions under MAS [1], we have tried toobserve 1H/14N correlation under fast MAS conditions using
a 1H/14N overtone HMQC method.[2] (Fig. 1) Since 1H-14N
overtone coherences build two-times quicker than those of
14N

fundamental transitions, use of 14N overtone pulse

potentially enhance the sensitivity. In addition, 14N overtone
transition is free from the first order quadrupolar broadening,eliminating the necessity of the precise magic angle
adjustment unlike fundamental 14N transition. Although
1H/14N correlations were successfully observed, the method

was suffered from limited excitation width of 14N overtone
pulse due to its slow nutation rate and thus long excitation

Fig.1 14N overtone/1H HMQC spectrum

pulse. We come up with the idea to utilize this band-limitedof glycine observed at 70 kHz MAS.

nature of 14N overtone pulse to selectively excite coherences
between 1H and a specific 14N nucleus.
N-H distance measurements: Although precise 1H-14N distance measurements can be made by using PMS-RESPDOR experiments by uniformly saturate all the 14N nuclei [3], the presence of multiple 14N sites
introduces complexity in data analysis. The use of 14N overtone pulse in S-RESPDOR allows us to selectively
determine the distance between a selected 1H-14N pair even in the presence of multiple nitrogen sites invicinity.[4] (Fig. 2)

Fig.2 (left) 1H/14N OT REDOR/RESPDOR sequence. S’ and S0 are observed with and without 14N OT
saturation pulse, respectively. (right) 1H/14N OT REDOR/RESPDOR fraction curve observed at two
different 14N OT frequencies. Selective distance measurements between NH3+ and NH were achieved.

－ 86 －

N-H correlation: The selective nature of 14N overtone pulse also allows frequency-swept approach torecord frequency response similar to historical CW NMR spectrometers. 1H-14N overtone S-RESPDOR gives
1

H resonances only if 14N overtone frequency hits the 14N nucleus which is dipolar-coupled with the 1H

nucleus. Thus, a set of 1H-14N overtone S-RESPDOR spectra with varying 14N overtone frequencies provides
1

H/14N overtone correlation spectra.[5] The method allows highly efficient observation of 1H/14N correlations

even for remote (non-bonded) 1H-14N pairs.

Fig. 3 Comparison of 1H/14N correlation spectra observed D-HMQC and RESPDOR.
In the RESPDOR approach, 1H S0-S’ spectra were plotted at various 14N OT frequencies.

References[1] L.A. O’Dell, C.I. Ratcliffe, Chem. Phys. Lett. 514 (2011) 168-173.
[2] Y. Nishiyama, M. Malon, Z. Gan, Y. Endo, T. Nemoto, J. Magn. Reson., 2013, 230, 160-164.
[3] N.T. Duong, F. Rossi, M. Makrinich, A. Goldbourt, M.R. Chierotti, R. Gobetto, Y. Nishiyama*, J.
Magn. Reson. 308 (2019) 106559.
[4] N.T. Duong, Z. Gan, Y. Nishiyama, Front. Mol. Biosci., 2021, 8, 645347.
[5] N.T. Duong, Y. Nishiyama, Phys. Chem. Chem. Phys., 2022, 24, 10717-10726.

－ 87 －

L3-5

றᆾƠſƆǀǖǬǕȞƣལെဗਸƨ෯ຍଅ஽g໣७ 0/4 ໐࿊ਸƨ༌ࡴମጫ૱్Ơƽǀशነ˕ᤶ ‫ݛ‬ӋɾԮࢃ୉ָʀ࿯੗෼࣯‫ॶڂݜ‬

Revealing cation disorder and hydrogen bonding in minerals via multi-nuclear NMR and
first-principles calculationżXianyu Xue1
1

Institute for Planetary Materials, Okayama University

Over the years, we have applied a combined approach of solid-state NMR and first-principles
calculation to unravel cation (Si/Al/Mg/Zn…) distributions, hydrogen distribution and hydrogen bonding
for a large number of important silicate and oxide minerals, in order to help understand their
physical/thermodynamic properties and stability. Here, I showcase our latest study on the Si/Al distribution
and hydrogen bonding of a nature mineral, ussingite (Na2AlSi3O8OH), which features a unique partiallyinterrupted framework structure and strong hydrogen-bonding. It will be demonstrated that a combined
comprehensive NMR and first-principles calculation unambiguously revealed the existence and correlationof Si-Al disorder and OH groups of both stronger and weaker hydrogen bonding than the ordered structure.
The ability to clearly reveal the correlation between Si/Al disorder and hydrogen-bonding strength opened
up exciting opportunity for greater understanding of crystal chemistry of minerals and inorganic materials.
Introduction
Cation order/disorder and hydrogen-bonding in minerals and related inorganic solid materials areimportant factors affecting their physical and chemical properties and stability. NMR spectroscopy is aunique tool to provide such information. The utilization of multi-nuclear and multi-dimensional NMR
techniques in combination with first-principles calculations greatly enhances the amount of informationthat can be extracted from minerals and inorganic materials of complicated disorder and defects.
Over the years, we have applied such an approach tounravel cation (Si/Al/Mg/Zn…) distributions, hydrogen
distribution, and hydrogen bonding in a large number ofimportant hydrous and nominally anhydrous silicate and oxideminerals, often synthesized at high pressure and temperature tosimulate the conditions of the interiors of the Earth (e.g., Xue& Kanzaki, 2009; Stebbins & Xue, 2014; Xue et al., 2016). We
recently also demonstrated the usefulness of NMR
spectroscopy for the study of cation (Ca/Ba) distribution in
calcite mineral (Marugata et al., 2022). Here, I will showcase
our latest study on the Si/Al distribution and hydrogen bondingof a nature mineral, ussingite (Na2AlSi3O8OH), which has aunique partially interrupted framework structure and featuresstrong hydrogen-bonding (see Fig. 1).
Fig. 1. Crystal structure of
In the structure of ussingite, there are four tetrahedral (T)4sites. T1 & T2 are Q (i.e., having 4 next nearest neighborussingite(NNN) T sites), and T3 & T4 are Q3 (i.e., having 3 NNN T
sites). The Si/Al distribution of their NNN environments are as
the following (in brackets): T1(1T2,1T3,2T4), T2(1T1,2T3,1T4), T3 (1T1,2T2), T4(2T1,1T2). Hydrogen
was found to be in the T4-O8-H···O2-T3 configuration, with a short hydrogen-bonding O8···O2 distance

Keywords: mineral, cation disorder, hydrogen bonding˕ ͢ΐ͓ ͢ΎΞ͑－ 88 －

(2.481 Å) (Williams & Weller, 2012). In the ordered structure, T1 is only occupied by Al, and the other Tsites are only occupied by Si. Previous X-ray and neutron diffraction (Rossi et al., 1974; Williams &Weller, 2012; Ribbe, 1974) and 1H, 29Si NMR studies (Oglesby & Stebbins, 2000; Johnson & Rossman,2004) gave contradictory conclusions as to whether Al-Si disorder exist, and which site Al is disordered
into. As many geologically and technologically important aluminosilicate glasses and melts are of partiallydepolymerized structures, constraining the Si-Al distribution in ussingite may provide a general crystal
chemical understanding of the partition behavior of Al in partially depolymerized aluminosilicate structure.
Furthermore, how the Si-Al disorder affects the behavior of strong hydrogen bonding is also of great crystal
chemical significance. In this study, I was able to unambiguously clarify the Si/Al distribution and its effecton the hydrogen bonding in ussingite via combined comprehensive NMR measurements and first-principles
calculation.
Methods
NMR measurements were performed on a natural ussingite sample from Lovozero alkali Massif,
Russia, initially using a Varian 9.4 T Unity-Inova spectrometer and 2.5 mm T3 MAS probe, andsubsequently using a Bruker 9.4 T Avance NEO spectrometer and a 3.2 mm MAS probe. First-principles
calculations (energy & NMR parameters) were performed with the GIPAW method using the QuantumESPRESSO package (v.7.0). Both the ordered ussingite structure and models for Si-Al disorder werestudied. For the latter, one pair of Al-Si exchanged between a T1 site and each of its NNN (1T2, 1T3 ,2T4), as well as between a pair of remote T1 and T2 sites in a 2x2x2 supercell (256 atoms) with were
examined. For each calculation, the crystal structure was first fully relaxed before NMR calculation. The
PAW-pseudopotential and PBEsol functional (from the PSlibary) was used.
Results & Discussion
1H-29Si CPMAS NMR of ussingite revealed three main peaks near -84, -88 and -96 ppm, which may be
attributed to Q3(1Si2Al), Q3(2Si1Al) and Q4(3Si1Al), corresponding, respectively, to T4, T3 and T2 site in
the ordered structure. These main peaks clearly each contain more than one component(s). In addition,
weak peaks near -81 and -92 ppm were also revealed, which may be, respectively, attributed to Q3(3Al)and Q3(3Si). These features can be accounted for only by Si-Al disorder between T1 and T2 sites, contrary
to previous speculations of disorder between T1 and T3 or lack of disorder. 1H MAS NMR revealed a main
peak near 13.8 ppm (with a shoulder near 13.3 ppm), a group of three partially resolved weaker peaks near
15.8, 15.5, 15.2 ppm, and another weaker peak near 11.0 ppm, similar to that reported for a sample ofdifferent locality (Johnson & Rossman, 2004). 2D 1H DQ MAS NMR confirmed that all these peaks belong
to the same structure. Furthermore, 2D 1H-29Si HETCOR NMR revealed that there are 4 components forthe group of proton peaks near 15 ppm, which are each correlated to two Si of the same number of nSi(3n)Al neighbors (two of them correlated with two Si(1Si2Al), and the other two with two Si(2Si1Al)), andthe proton peak near 11 ppm is correlated to Si(3Al) and Si(3Si). As in the ordered structure, each proton isassociated with one Si(1Si2Al) and one Si(2Si1Al), this observation indicates that the extra proton NMR
peaks near 15 and 11 ppm are due to OH groups which are either bonded or hydrogen-bonded to a Si sitethat is next to a disordered T site. Both the 29Si and 1H NMR data are consistent with about 3% Si-Al
disorder. 23Na and 27Al 3QMAS NMR data are also consistent with local structural disorder.
First-principles calculation support the above experimental observation and provide further insight into
the relationship between Si/Al disorder and hydrogen-bonding. The calculation revealed that Si-Al
exchange between NNN T1-T2 is energetically most favorable and thus the most plausible model; the othermodels with Si-Al exchange between NNN T1-T3, T1-T4, or remote T1-T2 sites, which are accompanied
by formation of Al-NBO (non-bridging oxygen), AlOH and/or Al-O-Al, gave higher energies (by 28~68
kJ/mol), consistent with the known unfavorable formation of Al-NBO and AlOH (relative to Si
counterparts) and Al avoidance principle. The calculated 29Si and 1H chemical shifts of the model with AlSi exchange between NNN T1-T2 agree well with the observed NMR data and the peak assignment
described above. The correlation between the Si/Al disorder and hydrogen-bonding distances is explainable
by the transmission of bond strength variation associated with Si/Al disorder to hydrogen-bonding distancevariation. To my knowledge, this is the first study that has clearly revealed such a relationship.
In conclusion, this study has unambiguously revealed the presence of about 3% Si-Al disorder between
T1 & T2 sites (both Q4) in ussingite, which is accompanied by the formation of OH of both stronger andweaker hydrogen bonding (larger and smaller 1H chemical shift). These results provided insights into thepartition behavior of Si-Al in partially depolymerized aluminosilicate structure and its relationship withhydrogen bonding strength.

－ 89 －

L3-6

Innovations in High-field Protein Solid-state NMR and
its Applications to Amyloid-E
E Fibrils and Other Biomolecules
Ayesha Wickramasinghe,2 Tatsuya Matsunaga,2 Isamu Matsuda,1 Mohammad Jafar
Tehrani,1 Hibiki Terami,1 Yoshiki Shigemitsu,1 Naohiro Kobayashi,2 and Yoshitaka
Ishii1,2*
1School of Life Science and Technology, Tokyo Institute of Technology,

Yokohama, Japan
2BDR Center, RIKEN, Yokohama, Japan

This study presents our ongoing efforts to advance high-field protein solid-state NMR (SSNMR) from
two aspects. First, we discuss applications of biomolecular SSNMR to amyloid E fibrils and other systems.
Second, we discuss our recent progress in biomolecular solid-state NMR (SSNMR) for resolution andsensitivity enhancement by 1H-detected SSNMR, ultra-fast magic angle spinning, and use of a highmagnetic field.[1, 2] We also demonstrate that traditionally time-consuming 3-5D biomolecular SSNMR is
feasible for signal assignments in a nano-mole-scale with this approach.

We first discuss our progress in structural examination of misfolded amyloid-ȕ $E) by SSNMR.
Increasing evidence suggests thatformation and propagation of misfolded
aggregates of 42-UHVLGXH$ȕUDWKHU
than more DEXQGDQW$ȕSURYRNHV
the Alzheimer’s cascade. Our SSNMR
study recently revealed a unique SVKDSHGVWUXFWXUHRI$ȕDP\ORLGILEULO
for the first time.1 Here, we discuss thefeasibility of characterizing thestructure of trace amounts of brainderived and synthetic amyloid fibrils by
sensitivity-enhanced 1H-detected solidstate NMR (SSNMR) under ultra-fastmagic angle spinning (UFMAS).2 Dataon cryoEM and SSNMR analysis of AE
fibril and NMR analysis of otherbiopolymers will be also presented.

Figure 1. (Right) High sensitivity 1H-detected 1H/13C 2D
SSNMR using UFMAS provided molecular fingerprints ofAE42 fibrils (200 Pg) templated from ~20 ng of brainderived amyloid fibrils from Alzheimer’s patient only after
9-min measurements.㸦Left㸧 A corresponding 2D spectrum
for synthetic AE42 fibril reveals distinctive spectralfeatures, demonstrating the presence of drastically different
molecular structures for brain-derived AE42 fibril.

Solid-state NMR㸪1H-detection, Ultra-fast MAS, Amyloid
Ayesha Wickramasinghe, Tatsuya Matsunaga, Isamu Matsuda, Mohammad Jafar Tehrani, Hibiki Terami,
Yoshiki Shigemitsu, Naohiro Kobayashi, Yoshitaka Ishii‫ۑ‬－ 90 －

Second, we discuss our recent progress in resolution and sensitivity enhancement in 1H-detected
ELRPROHFXODU66105XQGHU8)0$6FRQGLWLRQV N+] LQDKLJKPDJQHWLFILHOG 1H frequency t 700
MHz ).3,4 2XUGDWDRQSURWHLQPLFURFU\VWDO*%DQG$ȕILEULOVKRZWKDWWUDGLWLRQDOO\WLPH-consuming 3-5D
biomolecular SSNMR is feasible for signal assignments in a nano-mole scale with this approach. We also
discuss novel concepts for drastic sensitivity enhancement by various polarization-transfer schemes using
ultra-fast MAS.5 The progress of the JST MIRAI project to construct ultra-high field NMR will be briefly
outlined.
References:(1)

Xiao, Y.et al. Nat. Struct. Mol. Biol. 2015, 22, 499.

(2)

Wickramasinghe, A.et al. J. Am. Chem. Soc 2021, 143, 11462.

(3)

Wickramasinghe, N. P.et al. Nat. Methods 2009, 6, 215.

(4)

Ishii, Y.et al. J. Magn. Reson. 2018, 286, 99.

(5)

Matsunaga, T.; Matsuda, I.; Yamazaki, T.; Ishii, Y. J. Magn. Reson. 2021, 322, 106857.

－ 91 －

IL-1

NMR-Based Molecular Rheology for the Study of Chain
Motion in Complex Polymer Systems
Kay Saalwächter1, Anton Mordvinkin1, Marcus Suckow2, Diana Döhler3,
Frank Böhme2, Wolfgang H. Binder3, Ralph H. Colby4
1

Institut für Physik – NMR, Martin-Luther-Univ. Halle, Germany

2

IPF Dresden, Germany; 3Macromol. Chemistry, MLU Halle, Germany;

4

Penn State U, State College, USAPolymeric materials (including biomolecular samples) are characterized by molecular
dynamics covering a large timescale range, often accompanied by a complex morphology,
comprising phases with different molecular packing and vastly different mobility. Establishedhigh-resolution, mostly 13C-based solid-state NMR can play out its full power in elucidatingthese complexities, but at the expense of long experimental times. In this contribution, I
summarize the options provided by 1H low-resolution (possibly low-field) NMR in gathering
relevant information on the dynamics of polymer chains.
Dynamic information is mostly encoded in transverse spin evolution governed by the dipolar
coupling network [1]. Therefore, methods as simple as transverse relaxation measurements
can be used to characterize the dynamics qualitatively, e.g. distinguishing between rigid(glassy/crystalline) regions and mobile domains featuring large-scale segmental and chain
motion far above the glass transition. In the latter case, the dynamics is characterized bypower-law time correlation functions and local motional anisotropy, the latter leading to finite
residual dipolar couplings in the ten to few hundred Hz range. Also, these can be probed
quantitatively and be used to back up or disprove models in polymer physics aimed at anunderstanding of e.g. mechanical properties. To this end, proton multiple-quantum (MQ)
NMR has established itself as a more advanced, better analyzable version of transverse
relaxometry [1,2]. The two signal functions provided by this technique can be processed andfitted rather reliably, allowing for a separation of coherent spin evolution due to (residual)
dipolar couplings and incoherent transverse relaxation effects [3].
These principles are demonstrated in recent applications focusing on the chain dynamics intransient associating networks, which could possibly be applied as self-healing materials.
Specifically, we study the relations between the microscopic chain dynamics and themechanical behavior of transient elastomers based upon poly(isobutylene), PIB with “sticky”
side- or endgroups that form clusters in the nm range. The dynamics of the chains and of the
sticky groups were studied by a combination of dielectric spectroscopy (DS), 1H static MQ aswell as high-resolution MAS NMR, and are correlated with the rheological behavior.
The first material platform are butyl rubber ionomers with sparse imidazole-based sidegroups,
which show promise as self-healing elastomers [4,5]. For the first time, we have demonstrated
a quantitative agreement of the NMR-detected chain relaxation and the rheology results [5],
solid-state NMR, low-resolution multiple-quantum NMR, polymer dynamics－ 92 －WKXVFRQ¿UPLQJWKHVWLFN\UHSWDWLRQSLFWXUH>@The combined results suggest a hierarchicalmodel of sticker and chain dynamics as depicted in Fig. 1.

Figure 1. Hierarchy of (thermo)dynamic processes relevant for sticky chain dynamics in.self-healingelastomers as elucidated by a combination of 1H NMR, dielectric spectroscopy and rheology [5].

The second platform are telechelic linear and star-shaped PIBs carrying different hydrogenbonding moieties [7]. Here we could address the relation between the terminal time of theindividual chains and the onset of flow, which turn out to be equal [8]. Therefore, in this casethe one theory considering systems with clustered stickers [9] is disproven. The clusterrelated relaxation detected by DS is always much faster than the chain relaxation probed by
NMR. The overall trends suggest that all relaxations are dominated by a cluster-related
activation barrier, but also that the DS-based cluster relaxation cannot be directly associatedwith the sticker lifetime, in contradiction to the common assignment of the DS-detected
process [10]. We thus suggest a reconsideration of the assumptions made in explaining therelationship between molecular-scale and macroscopic dynamics in such transient elastomers.

References[1] K. Saalwächter, Progr. NMR Spectrosc. 51, 1 (2007)[2] K. Saalwächter, in: G.A. Webb (ed.), Modern Magnetic Resonance,
Springer, Cham (2017). DOI: 10.1007/978-3-319-28275-6_59-2[3] M. Mordvinkin, K. Saalwächter, J. Chem. Phys. 146, 094902 (2020);
erratum: J. Chem. Phys. 148, 089901 (2018)[4] Das, A. et al.; ACS App. Mater. Interf. 7, 20623 (2015)[5] Mordvinkin, M. et al.; Macromolecules 52, 4169 (2019)[6] Stukalin, E.B. et al.; Macromolecules 46, 7525 (2013)[7] Döhler, D.; Peterlik H.; Binder, W. H..; Polymer 69, 264 (2015)[8] Mordvinkin M. et al.; Phys. Rev. Lett. 125, 127801 (2020)[9] Semenov, A. N.; Rubinstein, M.; Macromolecules 35, 4821 (2002)[10] Gold, B.J. et al.; ACS Macro Lett. 6, 73 (2017).

－ 93 －

IL-2

Non-Covalent Secondary Bonding Interactions Examined
via Multinuclear Solid-State Magnetic Resonance
David L. Bryce1
University of Ottawa, Ottawa, Canada. A large proportion of the elements of the periodic table have isotopes amenable to study via
NMR spectroscopy. Similarly, in recent years the concept of element-based non-covalentinteractions, also known as secondary bonding interactions, has gained traction and attracted
much interest in a variety of communities. Analogous to the ubiquitous hydrogen bonds, otherinteractions such as halogen bonds, chalcogen bonds, pnictogen bonds, and tetrel bonds, forexample, have found applications in crystal engineering, supramolecular chemistry, catalysis,
and materials science. Here, I will describe our ongoing efforts to characterize and understandthese various classes of bonds via multinuclear solid-state NMR spectroscopy. For example,
we have applied 35/37Cl, 79/81Br, and 127I solid-state NMR and nuclear quadrupole resonance(NQR) spectroscopies to examine the NMR response of a variety of halogen bond donors uponbond formation. 77Se and 125Te magic-angle spinning (MAS) NMR has been used to understandthe impact of chalcogen bonding on the selenium and tellurium chemical shift tensors. 121Sb
quadrupolar coupling constants measured via NQR spectroscopy have been measured and used
in a rudimentary NQR crystallographic refinement protocol to obtain structural information on
novel materials prepared using mechanochemical approaches. Other recent work from ourlaboratory includes the in-situ monitoring of halogen bond formation in the solid state via 31P
MAS NMR. Deuterium NMR has been used to demonstrate the modulation of molecular
dynamics via halogen bonded networks in solids. Finally, we will describe a recent
comprehensive study of the NMR response of the tin tetrel bond, where in particular
J(119Sn,35Cl) couplings are shown to be valuable indicators of non-covalent bond formation
between tin and oxygen.











Non-covalent interactions; solid-state NMR; coupling constants－ 94 －

IL-3

Studying protein weak interaction by NMRNico Tjandra
Biochemistry and Biophysics Center, National Heart, Lung, and Blood Institute,
National Institutes of Health, Bethesda, U.S.A.

High resolution NMR is an invaluable tool to study weak biomolecular interactions. The ability for NMR toprovide both structural and dynamic information in a site-specific manner can uniquely be tailored to study
such interactions. Relaxation NMR based experiments, such as NMR R2 dispersion, Chemical Exchange
Saturation Transfer (CEST), Dynamic Exchange Saturation Transfer (DEST) and others are designed toprobe systems that undergo exchange processes at different time scales. While residual dipolar coupling(RDC) and residual chemical shift anisotropy (RCSA) can provide information on systems containing
multiple conformations in equilibrium. Moreover, paramagnetic relaxation enhancement (PRE), and pseudocontact shift (PCS) can also report on the existence of multiple states of a system. This large number ofdiverse NMR methods to study weak interactions, that span a large range of timescales and differentiallysensitive to distances, illustrates the advantage of solution NMR compared to other biophysical orbiochemical techniques.
We employed a subset of the above NMR approaches to study a paralog of phosphotransferase systems in E.
coli. These systems are important in metabolic and stress response processes. These phosphorylation use
structurally similar enzyme, Enzyme Isugar (EIsugar) for the sugar import and Enzyme INtr (EINtr) for the nitrogen
regulation. Furthermore, their substrates HPr and NPr for EIsugar and EINtr, respectively also have similar fold.
Despite similarity in the structures of the enzymes and their substrates these transfer pathways are very
specific in forming enzyme-substrate complex that results in phosphorylated substrate and show no reversible
phophotransfer. We used PRE to study the specificity of N terminal of EINtr (EINNtr):NPr complex formationby evaluating the formation of its encounter complexes. Our PRE data demonstrated the presence of
encounter complexes not only between EINNtr and its expected substrate NPr, but also with the unexpected
substrate HPr (Figure 1). Unlike NPr, HPr occupies encounter sites on EINNtr without the ability to form a
final stereospecific complex. By occupying the non-productive sites, HPr drives NPr transient interaction
towards the productive sites, which are closer to the specific binding site. This has a consequence ofenhancing the specific complex formation between NPr and EINNtr. Noting that the concentration of HPr isover 150 times higher than NPr in the cell, we postulated that the formation of competitive encounter between
structurally similar substrates and a target enzyme can be a mechanism to generate cross-regulation of its
activity.
We tested our above proposal for cross-regulation from weak encounter complex formation using a coarsegrained simulation (Figure 2). As it is still not clear whether the encounters involving non-cognate substrate
can have a cooperative or competitive role. The results of our simulation confirmed our proposal thatencounter complexes can be cooperative or competitive, thus increasing or lowering the effective binding
affinity of the specific complex under different conditions. Our findings raised an interesting possibility fororganism to take advantage of low affinity interactions to build fine-tuned signaling pathways.
To test the generality of our hypothesis, the use of weak encounter complexes as a mechanism for crossregulation, we are also studying an enzyme, SixA in the phosphotransfer system of the bacteria. This enzyme－ 96 －

was shown to dephosphorylate NPr, but shows no significant activity towards HPr. Consistent with our
hypothesis, titration with either NPr or HPr show chemical shift changes on SixA. The measured chemical
shift changes are quite small signifying weak interactions. We confirmed these interactions using PRE.
Similar to the observations in the EINtr case, the site of interactions between the two substrates don’t overlap.
More importantly these weak interaction sites are away from the SixA active site. We propose that we areobserving the sites associated with the substrates leaving the enzyme active site, which is reflective of its off
rate. Since we are seeing different “off” sites for NPr and HPr, it suggests that these two substrates might
have cross-regulation as observed for EINNtr. Future experiments will be aimed at testing this cross-regulation
action of NPr and HPr on SixA.

Figure 1. Paramagnetic relaxation enhancement on EINNtr upon addition of different
substrates. a) Normalized intensity between free EINNtr and after the addition of HPr E5C
mutant tagged with MTSL. b) Intensity ratio between free EINNtr in complex with wild typeNPr and EINNtr in complex with NPr T6C tagged with MTSL. c) The PRE of EINNtr and NPr
T6C-MTSL. The inset shows the structure of the complex between IENNtr and NPr with thedistinct domains of EIN indicated. The sample was reduced using ascorbic acid to serve as the
diamagnetic reference. Stars indicate residues which were broadened beyond detection. The
enzyme EINNtr structure is shown on the left, while the structures of HPr and NPr with thelocation of the MTSL tag are shown on the right. The domains Į, Į/ȕ, and C-terminal of
EINNtr are marked at the top of the panel a. The mutation site H356Q is also indicated.

－ 97 －

Figure 2. Coarse-grained model of EINNtr interaction with NPr and HPr. a) The structure of
the complex between EINNtr and NPr is shown on the left. The representation of the enzyme
and substrate used in the simulation is depicted on the right. Each amino acid in the EINNtr isrepresented by a sphere with an appropriate radius, while NPr or HPr is represented by asingle sphere with a radius equaled to their radius of gyration. b) The various processes being
considered in the simulation for NPr interaction onto EINNtr. The spin label on NPr is shownin orange stick on the left of panel a, and a small orange sphere on the right and in panel b. c)
Processes included in the simulation of HPr interaction with the enzyme.

－ 98 －

AL-1Clarification of the GPCR signaling mechanism based on
the function-related conformational dynamics
Takumi Ueda1
Graduate School of Pharmaceutical Sciences, The University of TokyoProteins exert their biofunctions with continuously changing their conformations. In relation
to this point, solution NMR methods provide quantitative information about the dynamics ofproteins over a wide range of frequencies, in aqueous solutions at near-physiologicaltemperatures. I have been utilized NMR for the structural elucidation of the functions of highmolecular weight proteins, including signaling of G protein-coupled receptors (GPCRs)1-7 andbacterial thermotaxis regulation proteins, conductivity regulation of ion channels8, electrontransport of photosynthetic membrane proteins9, and DNA repair reaction of photolyase.
GPCRs function as receptors of various chemical messengers, including
neurotransmitters, hormones, cytokines (chemokines), and metabolites, and more than 30% of
current drugs target GPCRs. NMR studies of GPCRs are challenging, because of their hugesize, low yield and stability, limited stable isotope labeling method in eukaryotic protein
expression systems, which are utilized in GPCR studies, thus the amount of information on theconformational dynamics of GPCRs is limited. To overcome these bottlenecks, we havedeveloped various methods for sample preparation, NMR measurement and data analyses, andapplied these methods to observe the function-related conformational equilibrium of GPCRs.
For example, we developed methods for determining the rate constants of sophisticatedconformational equilibrium models from NMR data using exchange Monte-Carlo algorithm2,
and methods for the sparse sampling and reconstruction of multidimensional NMR data, leading
to > 50% reduction of the measurement time of 2D NMR spectra5.
To address the mechanism underlying the unique characteristics in the signaltransduction of GPCRs, such as efficacy and biased signaling, we performed NMR analyses of
E2 adrenergic receptor (E2AR) and P opioid receptor (POR) bound to ligands with various
efficacies and biased factors4,7. Resonances from the residues in the transmembrane region of
E2AR and POR exhibited their chemical shifts, linewidths, and the number of signals dependent
on the efficacies of the ligands. Based on these results, we demonstrated that E2AR and POR
exists in equilibrium among multiple inactive and active conformations, and the populations of
the active conformation determine the ligand efficacy and biased signaling.
Under the physiological conditions, GPCR are embedded in the lipid bilayer of cells.
To address the effects of the lipid bilayer environment on the function and conformational
dynamics of GPCRs, we examined GPCRs embedded in the lipid bilayer of reconstituted highdensity lipoprotein (rHDL). We demonstrated that the population of the active conformationof E2AR in rHDL better correlates with the maximum cAMP response of the cells
expressingE2AR than in micelles6. In addition, we examined the effect of lipid compositionon the conformation and activities of adenosine A2A receptor (A2AAR)1. Our NMR analyses
revealed that A2AAR in the partial agonist-bound state exists in equilibrium between multiple

G protein-coupled receptor, membrane proteins,－ 100 －

active conformations and an inactive conformation, and that the full agonist drives theequilibrium toward the multiple active conformations. We quantified the G protein activation
by A2AAR in rHDLs, and determined that the DHA chains positively modulate the signaling
activity of A2AAR. The DHA chains in rHDLs did not affect the equilibrium between theinactive and active conformations, but redistributed the multiple active conformations of
A2AAR toward those preferable for G protein binding.
The timescales and populations of the function-related conformational equilibria,
determined by NMR, open an avenue for integrating information about the protein structures atatomic resolutions and the real-time observations of the cellular responses via GPCR signaling.
For example, a time-course simulation of G-protein signaling, based on the intracellularsignaling reaction rates and the exchange rates between the inactive and active conformationsof E2AR, demonstrated that the E2AR agonists induce the E2AR activation, G-protein activation,and the increase in cAMP on timescales of milliseconds, hundreds of milliseconds, and seconds,
respectively6. It is exciting to look forward to the construction of GPCR signaling models thatcan quantitatively explain real-time cellular responses at atomic resolution.
References(1) Mizumura, T., Kondo, K., Kurita, M., Kofuku, Y., Natsume, M., Imai, S., Shiraishi, Y., Ueda, T., and Shimada,
I. Activation of adenosine A2A receptor by lipids from docosahexaenoic acid revealed by NMR. Sci. Adv. 6,
eaay8544 (2020).
(2) Imai, S., Yokomizo, T., Kofuku, Y., Shiraishi, Y., Ueda, T., and Shimada, I. Structural equilibrium underlying
ligand-dependent activation of ȕ2-adrenoreceptor. Nat. Chem. Biol. 16, 430-439 (2020).
(3) Shimada I., Ueda, T., Kofuku, Y., Eddy, M., and Wüthrich, K. GPCR drug discovery, integrating solution NMR
data with crystal and cryo-EM structures. Nat. Rev. Drug Discov. 18, 59-82 (2019).
(4) Okude, J., Ueda, T., Kofuku, Y., Sato, M., Nobuyama, N., Kondo, K., Shiraishi, Y., Mizumura, T., Onishi, K.,
Natsume, M., Maeda, M., Tsujishita, H., Kuranaga, T., Inoue, M., and Shimada, I. Conformational equilibrium of
P-opioid receptor determines its efficacies and functional selectivities. Angew. Chem. Int. Ed. 54, 15771-15776(2015)(5) Ueda, T., Yoshiura, C., Matsumoto, M., Kofuku, Y., Okude, J., Kondo, K., Shiraishi, Y., Takeuchi, K., andShimada*, I. Development of a method for reconstruction of crowded NMR spectra from undersampled timedomain data. J. Biomol. NMR 62, 31-41 (2015)(6) Kofuku, Y., Ueda, T., Okude, J., Shiraishi, Y., Kondo, K., Mizumura, T., Suzuki, S., and Shimada, I. Functional
dynamics of deuterated E2 -adrenergic receptor in lipid bilayers revealed by NMR Spectroscopy. Angew. Chem.
Int. Ed. 53, 13376-13379 (2014)(7) Kofuku, Y., Ueda, T., Okude, J., Shiraishi, Y., Kondo, K., Masahiro Maeda, Hideki Tsujishita, and Shimada, I.
Efficacy of theE2-adrenergic receptor is determined by conformational equilibrium in the transmembrane region.
Nat. Commun. 3, 1045 (2012)(8) Minato, Y., Suzuki, S., Hara, T., Kofuku, Y., Kasuya, G., Fujiwara, Y., Igarashi, S., Suzuki, E., Nureki, O.,
Hattori, M., Ueda, T., and Shimada, I. Conductance of P2X4 purinergic receptor is determined by conformational
equilibrium in the transmembrane region, Proc. Natl. Acad. Sci. 113, 4741-4746 (2016)(9) Ueda, T., Nomoto, N., Koga, M., Ogasa, H., Ogawa, Y., Matsumoto, M., Stampoulis, P., Sode, K., Terasawa,
H., and Shimada, I. Structural basis of efficient electron transport between photosynthetic membrane proteins andplastocyanin in spinach revealed using nuclear magnetic resonance. Plant Cell 24, 4173-4186 (2012)－ 101 －

AL-2

Atomic-level elucidation of amyloid formation mechanism
by NMR spectroscopy㻌Daichi Morimoto1
㻝
Department of Molecular Engineering, Kyoto University㻌㻌㻌
Accumulation of abnormal protein aggregates is a common hallmark of Alzheimer’s disease and otherneurodegenerative disorders; the aggregates mainly consist of protein fibrils, i.e., amyloid fibrils. Despite thegrowing interest in their pathogenesis, the detailed formation mechanism remains elusive. To elucidate
general amyloid formation mechanism, we first investigated the aggregation propensities of ubiquitin chainsthat often include in protein aggregates observed in neurodegenerative diseases. We found that longer
ubiquitin chains were more likely to form amyloid fibrils and our NMR relaxation analysis showed that
intracellular ubiquitin binding receptors recognized polyubiquitin fibrils. To analyze formation ofpolyubiquitin fibrils in more detail, we have developed novel rheological NMR (Rheo-NMR) spectroscopy
to observe structural changes of proteins under shear conditions at atomic level and in real time. By using thedeveloped Rheo-NMR spectroscopy, we captured precise structural changes of polyubiquitin chains during
their amyloid formation. In addition, recently our Rheo-NMR simultaneously monitored structural changesof the folded and unfolded states of an ALS-related protein SOD1 in the amyloid formation processes.
Abnormal protein aggregation has often been
observed in neurodegenerative diseases including
Alzheimer’s

andParkinson’s

diseases.

Many

inclusion bodies associated with neurodegenerative
diseasescontainubiquitin,aposttranslational

modifier. Although this involvement of ubiquitin has
been reported since 1987, due to its extraordinarily
high structural stability it remains unclear why
ubiquitin is included in the pathological protein
aggregates.

By

using

differential

scanning

calorimetry (DSC), we found that the structural
stability of ubiquitin chains decreased with increasing
chain length (Fig. 1a)1. In addition, heat or shear stressFig. 1. Amyloid formation of polyubiquitin.
a, DSC curves for polyubiquitin chains ofdifferent length. b, EM image of polyubiquitin

induced amyloid formation of polyubiquitin chainsfibrils. c, Increase in 15N transverse relaxation

although monomeric ubiquitin does not form fibrils

rates of the UBA domain of p62 upon its(Fig. 1b)1. Intriguingly, also in cells polyubiquitininteraction with polyubiquitin fibrils. Morimoto,chains formed fibrillar aggregates depending on chain

et al. Nat Commun 2015 modified1.

length and their aggregates were selectively degraded by autophagy1. This result indicated that polyubiquitin
fibrils were recognized by autophagic receptors. Indeed, an autophagic ubiquitin receptor p62 wascolocalized with intracellular polyubiquitin fibrils. In addition, in the presence of polyubiquitin fibrils, 15N
transverse relaxation rates of p62 significantly increased, showing that p62 recognizes the fibrils (Fig. 1c)1.
㻌Amyloid, Rheo-NMR, in situ monitoring－ 102 －

To analyze amyloid formation of polyubiquitin in moredetail, we developed novel rheological NMR (RheoNMR) spectroscopy2. Although Rheo-NMR has been
established for polymer science in 1990, no Rheo-NMR
method had been applied to amyloid studies with
sufficient NMR sensitivity. To overcome the sensitivity
issue, we established a simple and versatile approach toRheo-NMR, in which the inner rod connected with aglass stick is inserted into the NMR sample tube in the
NMR instrument equipped with a cryogenic probe (Fig.
2a). Only the NMR tube is rotating by application ofFig. 2. Novel Rheo-NMR spectroscopy.

spinner spinning and the inner glass stick is stationary,a, Schematic diagram of the established Rheo-

producing an outer-rotating Couette cell (Fig. 2b). We

NMR instrument. b, Cross-section of the NMR

observed fibril formation of polyubiquitin in thesample tube in the Rheo-NMR instrument.

established Rheo-NMR instrument. Notably, during theMorimoto, et al. Anal Chem 2017 modified2.

fibril formation, we detected the chemical shift changes of the side chains of the residues at the edges of thealpha-helix and loops2. Thus, Rheo-NMR has the potential to capture structural changes during amyloid
formation in situ and at atomic resolution.
By using the established Rheo-NMR, we recently
analyzed amyloid formation of an ALS-related protein
superoxide dismutase 1 (SOD1)3. Under the moderately
denaturing condition, we simultaneously monitored
NMR signal decay of folded and unfolded SOD1. The
NMR signals of the folded species decreased faster thanthose of the unfolded one (Fig. 3a) and the 310-helix offolded SOD1 was found to be deformed prior to global
unfolding. In addition, we continuously measuredhydrogen exchange rates between amide protons of
SOD1 and water during the amyloid formation. The
amyloid-phase-dependent hydrogen exchange profiles
identified the residues involved in the core structureformation of SOD1 amyloid oligomers (Fig. 3b).

Fig. 3. In situ atomic-level monitoring ofamyloid formation of SOD1.
a, Peak intensity decay of folded (upper) and
unfolded (lower) SOD1 along its amyloid
formation. b, Change in hydrogen exchange
between amide protons of SOD1 and water inthe different phases of the amyloid formation.

References(1) Morimoto D, et al. (2015) The unexpected role ofpolyubiquitin chains in the formation of fibrillar

Iwakawa, Morimoto, et al. J Am Chem Soc 2021
modified3.

aggregates. Nat Commun. 6, 6116.
(2) Morimoto D, et al. (2017) High-sensitivity Rheo-NMR spectroscopy for protein studies. Anal Chem. 89(14),7286-7290.
(3) Iwakawa N, Morimoto D, et al. (2021) Multiple-state monitoring of SOD1 amyloid formation at single-residue
resolution by Rheo-NMR spectroscopy. J Am Chem Soc. 143(28), 10604-10613.

－ 103 －

HL-1

Pulse!
K. Takegoshi
Kyoto Univ. Kyoto, Japan
One of my delights as being an NMR spectroscopist is that I can manipulate coherence andmagnetization of nuclear spins by rf pulses at my will (to some extent…). A simple example ofsuch manipulation is found in the one pulse experiment; irradiation of a resonant rf pulse to aspin system at thermal equilibrium converts macroscopic longitudinal magnetization totransverse magnetizations (coherences), some of which evolves to induce current in the rf coilfor us to taste. The first and still most active/popular pulse "sequence" may be the Hahn-echo
sequence, which can refocus coherences of individual spin packets and form macroscopictransverse magnetization (spin echo). So far, I have developed several pulse sequences, mostof which are collated in Table 1. In this commemorative lecture, I would like to explain why
and how some of them were produced.
Table 1. Pulse sequences I have developed.
Ref. Abbreviation
Simple explanation
1
1)
TREV8
H homonuclear decoupling based on the magic echo
2)
TAPF
Modify the Hartman-Hahn condition for low J
3)
PFCT
Spin echo for AX spin systems
4)SR-1331
Self-refocused binominal sequences
5)
R2TR
X-X recoupling by rotational resonance in the TR frame
6)
MORE
X-Y recoupling by modulatory resonance
7)
FSLG-m2mm 1H-X recoupling by LG
8)RIR
X-X recoupling by resonant interference recoupling
1
9)
AM-TPPMH decoupling by amplitude-modulated TPPM
10) DARR
X-X recoupling by dipolar-assisted rotational resonance11) NOP
NOE to replace CP in solids
12) CPNZ
CP via non-Zeeman reservoirs
13) COCODARRCOSY+DARR (࡝ࡇࡸࡡࢇ)14) COMPOSER
CP using composite 0-degree pulses15) CPZ
CP among Z magnetizations using COMPOSER
116) DONUT
H decoupling/recoupling under double-nutation irr.
17) OD-CPZ
Rotational resonance for 1H-X heteronuclear pairs
NMR, rf pulse－ 104 －

Year
1985
1986
1989
1989
1995
1996
1999
1999
2001
2001
2002
2007
2008
2009
2014
2014
2017

References
1) Takegoshi, K. and C. A. McDowell (1985). "A "Magic Echo" Pulse Sequence for the HighResolution NMR Spectra of Abundant Spins in Solids." Chem. Phys. Lett. 116: 100-104.
2) Takegoshi, K. and C. A. McDowell (1986). "Cross Polarization Using a Time-Averaged
Precession Frequency. A Simple Technique to Reduce Radiofrequency Power Requirements
for Magnetization Transfer Experiments in Solids." J. Magn. Reson. 67: 356-361.
3) Takegoshi, K., et al. (1989). "A Perfect Spin Echo in a Weakly Homonuclear J-Coupled
Two Spin-1/2 System." J. Magn. Reson. 84: 611-615.
4) Takegoshi, K., et al. (1989). "Self-Refocused Binominal Pulse Sequence for Solvent
Suppression." J. Magn. Reson. 85: 198-202.
5) Takegoshi, K., et al. (1995). "Rotational Resonance in the Tilted Rotating Frame." Chem.
Phys. Lett. 232: 424-428.
6) Takegoshi, K., et al. (1996). "Modulatory resonance recoupling of heteronuclear dipolarinteractions under magic angle spinning." Chem. Phys. Lett. 260: 331-335.
7) Takegoshi, K. and T. Terao (1999). "13C-1H dipolar recoupling under very fast magic-angle
spinning using virtual pulses." Solid State Nucl. Magn. Reson. 13: 203-212.
8) Takegoshi, K., et al. (1999). "13C-13C polarization transfer by resonant interference
recoupling under magic-angle spinning in solid-state NMR." Chem. Phys. Lett. 307: 295-302.
9) Takegoshi, K., et al. (2001). "1H decoupling with third averaging in solid NMR." Chem.
Phys. Lett. 341: 540-544.
10) Takegoshi, K., et al. (2001). "13C-1H dipolar-assisted rotational resonance in magic angle
spinning NMR." Chem. Phys. Lett. 344: 631-637.
11) Takegoshi, K. and T. Terao (2002). "13C nuclear Overhauser polarization nuclear
magnetic resonance in rotating solids: Replacement of cross polarization in uniformly 13Clabeled molecules with methyl groups." J. Chem. Phys. 117: 1700-1707.
12) Ohashi, R., et al. (2007). "Cross polarization via the non-Zeeman spin reservoirs underMAS." Solid State Nucl. Magn. Reson. 31: 115-118.
13) Fukuchi, M. and K. Takegoshi (2008). "Combination of 13C-13C COSY and DARR
(COCODARR) in solid-state NMR." Solid State Nucl. Magn. Reson. 34: 151-153.
14) Fukuchi, M., et al. (2009). "Efficient Cross-3RODUL]DWLRQ8VLQJD&RPSRVLWHÛ3XOVHIRU
NMR Studies on Static Solids." J. Magn. Reson. 196: 105-109.
15) Kamihara, T., et al. (2014). "COMPOZER-based longitudinal cross-polarization via
dipolar coupling under MAS." J. Magn. Reson. 245: 94-97.
16) Takeda, K., et al. (2014). "Proton decoupling and recoupling under double-nutation
irradiation in solid-state NMR." J. Chem. Phys. 141: 224202-224201-224208.
17) Kamihara, T. and K. Takegoshi (2017). "Rotational resonance for a heteronuclear spinpair under magic-angle spinning in solid-state NMR." J. Chem. Phys. 146: 154202-154201154213.

－ 105 －

HL-2

Tips to prevent aggregation and denaturation ofproteins/peptides in solution NMRKaori Wakamatsu
Gunma University, Kiryu, Gunma, Japan.

Aggregation of proteins/peptides is one of the annoying problems in solution NMR studies.
At higher temperature, in which better resolution and sensitivity are expected, proteins tend toaggregate more rapidly. In addition, titration experiments to determine the residues involvedin the intermolecular interaction are often hindered by the formation of non-specific large
aggregate particles, although each component may be stable and in a monomeric state insolution in the absence of the interacting partner. In this talk, I would like to share, with you,tips to prevent aggregation (and denaturation) of proteins, peptides, and their complexes.
There are many causes that lead to the aggregation of proteins under conditions specific to
NMR. 1. Silicate in D2O; long year ago, silicate was employed to precipitate proteins forconcentration. 2. Surface of glass NMR tubes; silanol groups on very clean glass surface bindto peptide bonds. 3. Chemical shift reference compounds containing silicon atom such as
DSS; DSS is reported to bind with peptides containing a high amyloidgenic Aȕ1-40. These
problems are prevented: 1. by passing D2O through mixed-bed ion-exchange resin, 2. bypassivating the glass surface with dichlorodimethylsilane followed by quenching withmethanol, 3. by using dioxane or DMSO as the reference.
The (co-)aggregation of proteins and peptides containing the sequence with highamyloidgenic tendency may be prevented by using solvents of low ionic strength (to increase
repulsive electrostatic interactions), by appending Gly residue, or by adding non-detergent
sulfobetaines (NDSBs, Fig. 1), more specifically, choline-O-sulfate (COS) to the solvent.

Fig. 1. Structure of NDSBsAggregation, Binding analysis, Denaturation, Stabilization
－ 106 －

The effect of NDSB-195 to facilitate the mild solubilization of proteins was reported by
Vuillard et al. in 1995. His group later reported chemical synthesis of various NDSBs andtheir favorable effects: prevention of denaturation and aggregation of proteins, facilitation ofprotein refolding and crystallization. We synthesized other NDSBs in a somewhat systematicmanner, containing ammonium groups of different sizes and a sulfate group rather than theoriginal sulfonate group (Fig. 1), to compare their effects on denaturation, aggregation, andrefolding of proteins. It should be kept in mind that denaturation and aggregation are different
phenomena and different precautions are needed.
As for the prevention of denaturation of soluble proteins (hen egg white lysozyme, RNase A,
and cytochrome c), the strongest effect was observed for NDSB-181, which contains thesmallest ammonium group and a sulfonate group. Its stabilizing effect is stronger than that of
the most effective natural compatible osmolyte, trimethylamine-N-oxide (TMAO). On theother hand, m2 muscarinic acetylcholine receptor (m2R), one of GPCRs was best stabilized
by NDSB-265O, which contains largest ammonium group and a sulfate group both in the
non-solubilized (membranous) and the detergent-solubilized states. NDSBs with smaller
ammonium group and a sulfonate group, such as NDSB-195, stabilized m2R, but their effects
are weaker than NDSB-265O. In contrast to soluble proteins, not all GPCRs were stabilized
by NDSBs or osmolytes: Mu opioid receptor was VWDELOL]HGE\1'6%VOLNHP5EXWȕ2-ADR
and bacteriorhodopsin were destabilized by any of NDSBs and by osmolytes. The reason forthese differential effects on membrane proteins is elusive at present.
As for the prevention of aggregation of soluble proteins, the strongest effect was observed for
NDSB-265O but this compound has a strong denaturing effect on soluble proteins. I would liketo recommend NDSB-181 and -195 for the prevention of aggregation of proteins (not peptides),because these compounds exhibit both anti-aggregation and anti-denaturation effects.
The strong effect of COS to prevent aggregation of proteins and peptides containing thesequence with a high amyloidgenic tendency may well be ascribed to the large negative chargeof a sulfate group compared with a sulfonate group. This large negative charge will promote
the association of COS to peptide bonds, preventing the amyloid-like association of peptide
segments. The addition of COS enabled the successful titration analysis of the binding of aspinophilin fragment and an Į2A-ADR fragment, the latter containing an amyloidgenic sequence.
One may suspect that the addition of NDSBs have adverse effects on NMR measurements andthe interaction of biomolecules. However, properly purified NDSBs do not affect pulse widths
because they do not affect the ionic strength of the solution. Their specific viscosity is muchsmaller than that of glycerol. The apparent dissociation constant (Kd) of the interaction of
NDSB-195 with acidic fibroblast growth factor ranged from 0.04 to 3 M; sufficiently strong
interactions (with Kd < 1 mM) will not be affected by NDSBs. In fact, the activation of GĮi1
by m2-R was not affected by NDSBs. Noises originating from strong proton resonances of
NDSBs can be eliminated by deuterating NDSBs; at least deuterated COS is commerciallyavailable. In addition, deuterated COS can be easily recycled after experiments.

－ 107 －

ਸ਼3঩৯
11া10঩‫ق‬਽‫ك‬঩মୁ७ॵ३ঙথ

Day 3
Thursday, 10th Nov.
Japanese Sessions

L4-1

Gࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయE2ARࡢࣜ࢞ࣥࢻ౫Ꮡⓗάᛶ໬ᶵᵓ
‫ۑ‬௒஭㥴㍜㸪ᶓ⁁ᬛ㈗1,2, ᖾ⚟⿱2, ⓑ▼ຬኴ㑻1, ୖ⏣༟ぢ2, ᔱ⏣୍ኵ1
1 ⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮
2 ᮾி኱Ꮫ኱Ꮫ㝔⸆Ꮫ⣔◊✲⛉Structural equilibrium underlying ligand-dependent activation of ȕ2-adrenoreceptor‫ۑ‬Shunsuke Imai1, Tomoki Yokomizo1,2, Yutaka Kofuku1, Yutaro Shiaraishi1, Takumi Ueda2, Ichio
Shimada1
1 RIKEN BDR
2 Department of Pharmaceutical Science, The University of Tokyo

G-protein-coupled receptors (GPCRs) are seven-transmembrane proteins mediating cellular signals in
response to extracellular stimuli. Although three-dimensional structures showcase snapshots that can be
sampled in the process and nuclear magnetic resonance detects conformational equilibria, the mechanism bywhich agonist-activated GPCRs interact with various effectors remains elusive. Here, we used paramagnetic
nuclear magnetic resonance for leucine amide resonances to visualize the structure of ȕ2-adrenoreceptor in
the full agonist-bound state, without thermostabilizing mutations abolishing its activity. The structure
exhibited a unique orientation of the intracellular half of the transmembrane helix 6, forming a cluster of Gprotein-interacting residues. These results provide a structural basis for the dynamic activation of GPCRs
and shed light on GPCR-mediated signal transduction.
Gࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయ㸦GPCR㸧ࡣ7ᅇ⭷㈏㏻ᆺࡢ⭷ࢱࣥࣃࢡ㉁࡛࠶ࡾࠊ⣽⬊እഃ࡬ࡢసື⸆
ࡢ⤖ྜ࡟ࡼࡗ࡚άᛶ໬ࡍࡿ࡜ࠊ⣽⬊ෆഃ࡛Gࢱࣥࣃࢡ㉁ࡸ࢔ࣞࢫࢳࣥ࡜࠸ࡗࡓ✀ࠎࡢ࢚ࣇ࢙ࢡࢱ
࣮࡜┦஫స⏝ࡍࡿࡇ࡜࡟ࡼࡗ࡚ࠊ⣽⬊ෆ࡟ࢩࢢࢼࣝࢆఏ㐩ࡍࡿࠋࡇࢀࡲ࡛ࡢ⁐ᾮNMRゎᯒ࠿ࡽࠊ
GPCRࡢάᛶࢆ⌮ゎࡍࡿࡓࡵ࡟ࡣࠊ᫬㛫㍈ࡢせ⣲ࢆ⪃៖ࡋࡓᵓ㐀㸦ືⓗᵓ㐀㸧ࡢほⅬࡀᚲ㡲࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀ࡚࠸ࡿ[1]ࠋ୍᪉ࠊࡇࢀࡲ࡛࡟X⥺⤖ᬗᵓ㐀ゎᯒࡸࢡࣛ࢖࢜㟁Ꮚ㢧ᚤ㙾ゎᯒ࡟ࡼࡗ࡚
ゎ࠿ࢀࡓࡉࡲࡊࡲ࡞GPCRࡢ❧యᵓ㐀ࡣࠊάᛶࢆኻࢃࡏࡿࡼ࠺࡞⇕Ᏻᐃᛶኚ␗ࡢᑟධࡸ⣽⬊ෆഃ࡬
ࡢᢠయࡸGࢱࣥࣃࢡ㉁ࡢ⤖ྜ࡟ࡼࡗ࡚GPCRࡀᏳᐃ໬ࡉࢀࡓ᮲௳࡛ࡢࡳゎᯒࡉࢀ࡚࠸ࡿࠋࡇࡢࡓࡵࠊ
✀ࠎࡢ࢚ࣇ࢙ࢡࢱ࣮࡜┦஫స⏝ࡍࡿࠊసື⸆⤖ྜ≧ែ࡛άᛶ໬ࡋࡓGPCRࡢᵓ㐀ࡣࠊGPCRࡢᶵ⬟࡟࡜ࡗ࡚ᮏ㉁ⓗ࡟㔜せ࡞≧ែ࡛࠶ࡿ࡟ࡶ㛵ࢃࡽࡎࠊᮍࡔ᏶඲࡟ࡣ⌮ゎ࡛ࡁ࡚࠸࡞࠸ࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊసື⸆ࡀ⤖ྜࡋ࡚άᛶ໬ࡋࡓ≧ែࡢGPCRࡀከᩘࡢ࢚ࣇ࢙ࢡࢱ࣮࡜┦஫స⏝࡛ࡁࡿᶵᵓࢆ
᫂ࡽ࠿࡜ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋ࡚ࠊసື⸆⤖ྜ≧ែGPCRࡢ⁐ᾮNMRゎᯒࢆ⾜ࡗࡓ[2]ࠋ
ࡲࡎࠊGPCRࡢ୍✀E2࢔ࢻࣞࢼࣜࣥཷᐜయ (E2AR)ࡢLeuࡢ୺㙐࢔࣑ࢻᇶࢆࠊD఩࡜E఩ࢆ㔜Ỉ⣲໬ࡋࡓ[2,3,3-2H,15N]-Leuࢆ⏝࠸࡚㑅ᢥⓗ࡟15NᏳᐃྠ఩యᶆ㆑ࡋࠊࡑࡢ1H-15N TROSYࢫ࣌ࢡࢺࣝࢆ
ᐃࡋࡓࠋࡑࡢ⤖ᯝࠊィ28ṧᇶࡢLeu࡟ᑐࡋ࡚ࠊάᛶࢆ㜼ᐖࡍࡿ㏫సື⸆⤖ྜ≧ែ࡛ࡣ23ಶࡢࠊάᛶ
ࢆ㈿άࡍࡿసື⸆⤖ྜ≧ែ࡛ࡣ19ಶࡢࢩࢢࢼࣝࡀࠊࡑࢀࡒࢀほࡉࢀࡓࠋࡇࢀࡽ඲࡚ࡢࢩࢢࢼࣝ

ࢆኚ␗యゎᯒ࡟ࡼࡾᖐᒓࡋࠊᖖ☢ᛶ⦆࿴ಁ㐍 (PRE) ຠᯝ࡟ࡼࡿᵓ㐀ゎᯒ࡟⏝࠸ࡓࠋ⣽⬊ෆഃࡢH8࣊ࣜࢵࢡࢫୖࡢI334ࢆCys࡟⨨᥮ࡋࡓI334Cኚ␗యࢆㄪ〇ࡋࠊࢫࣆࣥࣛ࣋ࣝヨ⸆MTSL࡟ࡼࡗ࡚㒊఩㑅ᢥⓗ࡟ಟ㣭ࡋࡓࠋᑟධࡋࡓࢫࣆࣥࣛ࣋ࣝ࠿ࡽࡢ㊥㞳ࢆ཯ᫎࡍࡿࠊᖖ☢ᛶຠᯝ࡟ࡼࡿᶓ⦆࿴㏿ᗘ⭷ࢱࣥࣃࢡ㉁ࠊGࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయࠊᖖ☢ᛶ⦆࿴ಁ㐍ຠᯝ‫ࡅࡍࢇࡹࡋ࠸ࡲ࠸ۑ‬㸪ࡼࡇࡳࡒ࡜ࡶࡁࠊࡇ࠺ࡩࡃࡺࡓ࠿ࠊࡋࡽ࠸ࡋࡺ࠺ࡓࢁ࠺ࠊ࠺࠼ࡔࡓࡃࡳࠊ
ࡋࡲࡔ࠸ࡕ࠾

－ 110 －

ࡢቑศ*2ࢆ⟬ฟࡋࡓ⤖ᯝࠊ
㏫సື⸆⤖ྜ≧ែ࡟࠾࠸࡚ࡣᑐᛂࡍࡿ⤖ᬗᵓ㐀࠿
ࡽ㏫ィ⟬ࡋࡓ್࡜Q-factor
0.15࡜୍⮴ࡋࡓࡢ࡟ᑐࡋࠊ
సື⸆⤖ྜ≧ែ࡛ࡣࠊసື
⸆࡜Gࢱࣥࣃࢡ㉁ࡀ⤖ྜࡋ
ࡓE2ARࡢ⤖ᬗᵓ㐀࠿ࡽ㏫ィ ⟬ ࡋ ࡓ ್ ࡜ ࡣ Q-factor
0.46࡜୍⮴ࡋ࡞࠿ࡗࡓࠋࡇ
ࡢ⤖ᯝࡣࠊసື⸆⤖ྜ≧ែ
ࡢE2ARࡢᵓ㐀ࡀࠊ᪤Ꮡࡢ❧యᵓ㐀࡛ࡣㄝ࡛᫂ࡁ࡞࠸
ࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋࡑࡇ
࡛ࠊI334࡟ຍ࠼࡚E2ARࡢ⣽⬊ ෆ ഃ ࡟ Ꮡ ᅾ ࡍ ࡿ A59,
T136, N148, L266ࢆࡑࢀࡒࢀCys࡟⨨᥮ࡋࡓィ5✀㢮ࡢኚ␗యࢆㄪ〇ࡋࠊࡑࡢ
MTSLಟ㣭య࡟ほࡉࢀࡿ Fig. A: PRE analyses of E AR in the full agonist-bound state. Bar and2PREຠᯝࢆࠊసື⸆⤖ྜ≧ line graphs represent the experimental and back-calculated *2 values,ែ࡟࠾࠸࡚ほ ࡋࡓࠋᚓࡽ respectively. B: Intracellular views of the E2AR structures. Spheres
represent the residues that interact with the G proteins.
ࢀࡓィ 86ಶࡢ *2 ್ࢆ㊥㞳ᣊ᮰᮲௳࡜ࡋ࡚ࠊGPCRᵓ㐀㛫࡛ኚ໬ࡢ኱ࡁ࠸⭷㈏㏻࣊ࣜࢵࢡࢫ(TM)6ࢆྍືᇦ࡜ࡋࡓsimulated
annealingᵓ㐀ィ⟬ࢆ⾜ࡗࡓ࡜ࡇࢁࠊQ-factor 0.23࡜ᐇ㦂್ࢆ‶ࡓࡍᵓ㐀ࡀᚓࡽࢀࡓ(Fig. A)ࠋᚓࡽࢀ
ࡓᵓ㐀࡟࠾࠸࡚ࠊTM6ࡣࡑࡢ⣽⬊ෆഃࡀ90ᗘᅇ㌿ࡋࠊTM3,5,7࡜᥋ࡍࡿ࡜࠸࠺ࠊ᪤▱ࡢGPCRᵓ㐀࡟ࡣ࡞࠸≉ᚩࢆ᭷ࡋ࡚࠸ࡓࠋࡇࡢᅇ㌿࡟ࡼࡗ࡚TM6ୖࡢGࢱࣥࣃࢡ㉁⤖ྜṧᇶࡀTM3, 5ୖࡢGࢱࣥࣃࢡ㉁⤖ྜṧᇶ࡜ࢡࣛࢫࢱ࣮ࢆᙧᡂࡍࡿࡇ࡜࠿ࡽࠊࡇࢀࡀసື⸆ࡀ⤖ྜࡋࡓ≧ែࡢGPCRࡀGࢱࣥࣃࢡ㉁࡜⤖ྜ࡛ࡁࡿせᅉ࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓ(Fig. B)ࠋྜࢃࡏ࡚ࠊసື⸆⤖ྜ≧ែ࡟࠾࠸࡚໬Ꮫ
஺᥮࡟ࡼࡗ࡚ᗈᖜ໬ࡍࡿLeuṧᇶࡣࠊ⭷㈏㏻㡿ᇦࡢ࢚ࣇ࢙ࢡࢱ࣮⤖ྜ㒊఩ࢆྵࡴ㡿ᇦ࡟Ꮡᅾࡍࡿࡇ
࡜࠿ࡽࠊసື⸆⤖ྜ≧ែ࡟࠾࠸࡚ࡇࡢ㡿ᇦ࡟㢧ⴭ࡞㐠ືᛶࡸᵓ㐀ከᆺࡀᏑᅾࡍࡿࡇ࡜ࡶ᫂ࡽ࠿࡜
࡞ࡗࡓࠋ9⟠ᡤࡢ⇕Ᏻᐃᛶ࡬ࡢኚ␗ࡢᑟධ࡟ࡼࡾάᛶࢆኻࡗࡓE2AR࡛ࡣసື⸆⤖ྜ≧ែ࡟࠾࠸࡚
ࡶṧᇶᩘ࡟ᑐᛂࡍࡿࢩࢢࢼࣝࡀほ ࡉࢀࡓࡇ࡜࠿ࡽࠊࡇࡢ㡿ᇦࡢ㐠ືᛶࡣࠊGPCRࡀ✀ࠎࡢ࢚ࣇ࢙
ࢡࢱ࣮࡜⤖ྜࡋάᛶ໬ࡍࡿᶵ⬟࡟┤⤖ࡍࡿࡶࡢ࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋࡇࡢࡼ࠺࡞ᶵ⬟ୖ㔜せ࡞
ືⓗᛶ㉁ࡀࠊࡑࡢᵓ㐀ࢆX⥺ᅇᢡἲࡸࢡࣛ࢖࢜㟁Ꮚ㢧ᚤ㙾࡟࡚Ỵᐃࡍࡿࡇ࡜ࡀᅔ㞴࡞せᅉ࡛࠶ࡿྍ⬟ᛶࡀ࠶ࡿࠋࡇࢀ࡟ᑐࡋᮏ◊✲࡛ࡣࠊ⏕⌮ⓗ᮲௳࡟࠶ࡿࢱࣥࣃࢡ㉁ࢆࡑࡢࡲࡲࡢ≧ែ࡛ほ࡛ࡁࡿ⁐ᾮNMRἲ࡟ࡼࡗ࡚ࠊࡇࢀࡲ࡛୙࡛᫂࠶ࡗࡓసື⸆⤖ྜ≧ែࡢGPCRࡢᵓ㐀ࢆࠊࡑࡢᶵ⬟࡟┦㛵ࡋࡓ㐠ືᛶࢆᢚไࡏࡎ࡟ྍど໬ࡍࡿࡇ࡜ࡀ࡛ࡁࡓࠋ
References[1] Shimada I, Ueda T, Kofuku Y, Eddy MT, Wüthrich K, Nat Rev Drug Discov (2019) 18:59[2] Imai S, Yokomizo T, Kofuku Y, Shiraishi Y, Ueda T, and Shimada I., Nat Chem Biol (2020) 16:430－ 111 －

L4-2

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－ 112 －

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Fig. 2. Superimposed view of the 10 lowestenergy structures of the GB1 in living HeLa S3cells (gray) and those in PBS buffer (black).

15

Fig. 1. The H- N SOFAST-HMQC spectrum of
GB1 in living HeLa S3 cells measured in 2 min.

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－ 114 －

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         L5-1

NMR Spectra Recognition with Neural Networks and Deep
Learning‫ۑ‬ᒣෆ୍ኵ, ᏵᏊ㇦2, ⏑Ⳁ2, ⵓె⛥2, ⬌▱ᙪ2, ኱す⿱Ꮨ2, ⇃ᮌᗣ⿱2, ┦ἑᬛᗣ21Ἀ⦖⛉Ꮫᢏ⾡኱Ꮫ㝔኱Ꮫ࣭ᶵჾศᯒࢭࢡࢩࣙࣥ
2໭ᾏ㐨኱Ꮫ࣭኱Ꮫ㝔ඛ➃⏕࿨⛉Ꮫ◊✲㝔

NMR Spectra Recognition with Neural Networks and Deep Learning‫ۑ‬Kazuo Yamauchi1, Zihao Song2, Li Gan2, Jiaxi Jiang2, Zhiyan Hu2, Yuki Ohnishi2, Yasuhiro Kumaki2,
Tomoyasu Aizawa2
1

Instrumental Analysis Section, Okinawa Institute of Science and Technology

2 Faculty of advanced life science, Hokkaido university

The demand of simple and accurate chemical/biological analysis using analytical instruments by
non-experts is increasing. One of the typicalexamples is COVID-19 test by PCR by medical
professionals.

In such analytical works, it isimportant to build a system that does not depend onn Figure 1: Basic Components ("sample Preparation", "Measure
the abilities of a person involved in all aspects off-ment," and "Data Analysis”) of Instrumental Analysis Work.

"sample preparation", "measurement," and "data analysis” to have reliable results (Figure 1).
NMR as an analytical technique is no exception. The "sample preparation" for NMR is an inherently
relatively simple step, while other analytical methods often require chemical pre-treatment, modification, or
separation. NMR sample can basically be dissolved in a solvent, or measured as it is, which is a great
advantage of NMR. As for "measurement", it is possible to measure many samples in a short time with thesame condition, thanks to the continuous efforts of instrument manufacturers to develop and sale new models.
The most classical method of NMR "data analysis” is to assign each peak, to identify the functional group,and finally to identify the compound from the functional groups, which are all based on the researcher's
knowledge. Basically, this assignment procedure is the same for very small compounds to large proteins.
However, this method is not very independent. It is highly dependent on a person who works on the analysis,
there will be an immense difference of "data analysis” for the NMR professional and non-professional in thisclassical "data analysis” method. Alternatively, there are also other methods of "data analysis” besides thistype of classical assignment method. For example, there is a method using a database, but NMR spectra
analysis is still under development compared to other spectroscopy methods (e.g., Mass Spectrometry).
Another method is using principal component analysis (PCA) in metabolomics NMR for the analysis of
NMR data, but it is limited and is not yet a universal method for analyzing all NMR spectra.
In this study, we are trying a different approach to NMR "data analysis" using machine learning torecognize spectra. Machine learning has been widely used and utilized in many fields in recent years, include
recognition of handwritten characters, structure prediction of synthetic compounds in chemistry, structure
Machine Learning, solid state NMR spectra, metabolomics NMR spectra‫࠾ࡎ࠿ࡕ࠺ࡲࡸۑ‬㸪ࡑࢇࡎࡣ࠾㸪࠿ࢇࡾ㸪ࡋࡻ࠺࠿ࡁ㸪ࡇࡋࡆࢇ㸪࠾࠾࡟ࡋࡺ࠺ࡁ㸪ࡃࡲࡁࡸࡍࡦࢁ㸪࠶࠸ࡊࢃ࡜ࡶࡸࡍ

－ 116 －

prediction from MS spectra in analytical chemistry, or metabolomics prediction in NMR. We use the same
approach as handwriting recognition to classify NMR spectra using neural networks of machine learning.
13
C solid state NMR FID data for adamantane Table 1 : NMR Data Library for Neural Network Work(175), glycine (151), and alanine (69) were used as Number of NMR Dataa library for this study. These data were measured

395 sample data (adamantane;175, glycine;151, alanine;69)

under various experimental conditions (Table 1). NMR Experiment Condition
All FID data were Fourier transformed on
Topspin4.0.9 with 8k real data points (SI=8k) toobtain a spectrum with only approximate phasecorrection. A total of 8k intensity points wereobtained for each spectrum, and one spectrum wastreated as an 8k-dimensional vector. These data

Instrument:
300MHz, 400MHz, 500MHz, 600MHz, 800MHz, 900MHz
Sample Volume (rotor diameter):
1mm, 1.3mm, 2.5mm, 3.2mm, 4mm, 7mm
Spinning Speed:
0Hz to 60kHz
Method:solid state 13C spectra (CPMAS, DDMAS, etc.)
Spectra Width:varied (roughly and typically 300ppm to -50ppm)
Number of Scans:variedwere used to construct and validate a neural network. Computation was performed using core-i5 3210M,
16GB RAM windows 10 PRO laptop computer. Data analysis platform/software was KNIME, with Python(anaconda) in the background, and the neural network library, Keras, was used.
To build the neural networks, number of nodes in the input layer is 8K, which is equal to SI, and thenumber of nodes in the output layer is 2 which is adamantane and glycine used for “Adamantane or Glycine
recognition” (adam-gly case). Addition to this, 3
hidden layers with 128 nodes for each hidden
layer are used as the first trial (Figure 2).
Totally random library data were used to build aneural network with random selection of 70%(223) as trainer and 3% (14) as parity. The
remaining 27% (89) were used as testing.
“Adamantane or Glycine or Alanine recognition”(adam-gly-ala case) were also performed using
the same manner.

Figure 2: Schematic Illustration of Neural Network Architecture.
(8k input layer nodes, 3 hidden layers with 128 nodes for eachhidden layers, two output layers are shown as the example)

As the summary of testing results, 85 out of 89 data gave right answer in the adam-gly case and 97 out of
108 data were correct in the adam-gly-ala case, and the accuracy was 96% and 90%, respectively. Cohen's
kappa, which is used to evaluate the agreement of machine learning, was 0.908 and 0.836, respectively.
Furthermore, the accuracy by changing the number of layers in the hidden layer, the number of nodes in thehidden layer, and the number (percentage) of trainer data for the optimization of this neural network. To
reduce the computational cost and to avoid over-learning, 3 hidden layer, 32 nodes in the hidden layer, and
70% trainer data (that is, as many as possible) was found to be appropriate "with this adam-gly case".
This work showed an example of using the recognition of the NMR spectrum itself as a method of data
analysis and we found that NMR data is an "affordable" data size and easy to handle, from a machine learningperspective, and it can achieve over 90% recognition rate even this easy trial. This example is for very simple
NMR spectra of pure chemicals, but this method, spectrum recognition using machine learning, will not limit
only this case. In the presentation, we will also show an example of actual samples.
As the next step, it is necessary to optimize machine learning so that more accurate recognition of NMR
data. In addition, the only major challenge is that it needs many NMR data even lower sensitivity than otheranalytical methods, so it may require to develop the new measurement method and the hardware for it.

－ 117 －

L5-2

MOF㓄఩Ꮚࡢᅇ㌿࡜┦㛵ࡋࡓCO2ࡢ྾╔ࢲ࢖ࢼ࣑ࢡࢫ
‫ۑ‬ᰩཎᣅஓࠊ≟㣫 ᐀ᘯ2ࠊỈ㔝 ඖ༤3,41㔠ἑ኱Ꮫ⌮ᕤ◊✲ᇦ
2ᚨᓥ኱Ꮫ኱Ꮫ㝔♫఍⏘ᴗ⌮ᕤᏛ◊✲㒊
3㔠ἑ኱Ꮫࢼࣀ࣐ࢸࣜ࢔ࣝ◊✲ᡤ
4㔠ἑ኱Ꮫ᪂Ꮫ⾡๰ᡂ◊✲ᶵᵓ

Dynamics of adsorbed CO2 related to rotational motion of ligands in a metal–organic
framework‫ۑ‬Takuya Kurihara1, Munehiro Inukai2, Motohiro Mizuno3,4
1

Graduate School of Natural Science and Technology, Kanazawa University

2 Graduate School of Technology, Industrial and Social Science, Tokushima University
3 Nanomaterials Research Institute, Kanazawa University
4 Institute for Frontier Science Initiative, Kanazawa University

Metal–organic frameworks (MOFs) are promising porous materials for CO2 capture and separation.
Investigation of the adsorption and diffusion dynamics of CO2 in MOFs is essential for understanding theCO2 capture mechanism and improving the separation performance. In this work, by conducting solid-state
NMR under 0–1 MPa CO2 atmosphere, we show that CO2 adsorption and diffusion are affected by thevariable steric hindrance of rotative ligands in the narrow pores of a MOF. 13C CSA pattern and 2H
quadrupolar line shape analyses revealed that adsorbed CO2 hinders the ligand rotation. 13C exchange NMR
observed very slow CO2 diffusion related to the mobility of the ligands.
Introduction㔠ᒓ–᭷ᶵᵓ㐀య (MOF) ࠾ࡼࡧከᏍᛶ㓄఩㧗ศᏊ (PCP) ࡣ⣽Ꮝࢆ᭷ࡍࡿ㔠ᒓ㘒య࡛࠶ࡾࠊCO2ࢆࡣࡌࡵ࡜ࡋࡓ

ᐊຠᯝ࢞ࢫࡢศ㞳࡞࡝࡬ࡢᛂ⏝ࡀᮇᚅࡉࢀ࡚࠸ࡿࠋ㦵᱁ࢆᙧᡂࡍࡿ㔠ᒓ࢖࢜ࣥ࡜㓄఩Ꮚࡢ⤌ࡳྜࢃࡏ࡟ࡼࡾከᙬ࡞ᵓ㐀ࡀタィྍ⬟࡛࠶ࡾࠊࡇࢀࡲ࡛࡟ᩘከࡃࡢᵓ㐀ࡀྜᡂࡉࢀࠊ
ࡲࡓࡑࡢ࢞ࢫ྾╔ࡢ࣓࢝ࢽࢬ࣒ࡀ◊✲ࡉࢀ࡚ࡁࡓࠋMOF⣽Ꮝ୰࡛ࡣࠊ㓄఩Ꮚࡢࣇ࢙ࢽࣝᇶ➼ࡀࡋࡤࡋࡤᅇ㌿㐠ືࢆࡍࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࠋࡇ࠺ࡋࡓ㐠ືࡣ⣽Ꮝࡢᙧ≧ࢆኚ໬ࡉࡏࡿࡓࡵࠊ࢞ࢫ
ศᏊࡢ྾╔࣭ᣑᩓࢲ࢖ࢼ࣑ࢡࢫ࡟ᙳ㡪ࢆ୚࠼ࠊࡋࡓࡀࡗ࡚MOFࡢ࢞ࢫศ㞳⬟࡟㛵ࢃࡿྍ⬟ᛶࡀ࠶ࡿࠋࡋ࠿ࡋ࡞ࡀࡽࠊࢤࢫࢺ྾╔ࡀ㓄఩Ꮚࡢ㐠ືᛶ࡟ᙳ㡪ࡍࡿᵝᏊࡣほࡉࢀ࡚࠸ࡿࡶࡢࡢࠊ㓄఩Ꮚࡢᅇ㌿ࡀࢤࢫࢺศᏊࡢࢲ࢖ࢼ࣑ࢡࢫ࡟ᙳ㡪ࢆ୚࠼ࡿ࠿࡝࠺࠿ࡣࠊࡇࢀࡲ࡛࡟᫂ࡽ࠿࡟ࡉࢀ࡚࠸
࡞࠿ࡗࡓࠋᮏ◊✲࡛ࡣࠊcavity㒊఩࡜ࡑࢀࡽࢆ㐃⤖ࡍࡿwindow㒊఩࠿ࡽᡂࡿ1ḟඖ⣽ᏍࢆᣢࡘMOF
࡛࠶ࡿCID-Me ([Zn(5-methylisophthalate)(4,4’-bipyridyl)]n; Fig. 1) ࡟ὀ┠ࡋࠊwindow㒊࡟఩⨨ࡍࡿ㓄఩Ꮚbpyࡢᅇ㌿㐠ື࡜⣽Ꮝ୰࡟ྲྀࡾ㎸ࡲࢀࡓCO2ࡢ྾╔࣭ᣑᩓࢲ࢖ࢼ࣑ࢡࢫࡢ┦㛵ࢆࠊ࢞ࢫ㞺ᅖẼୗ࡟࠾ࡅࡿᅛయNMR ᐃ࡟ࡼࡾ᳨ウࡋࡓࠋ13C࠾ࡼࡧ2H NMR࡟ࡼࡿ㐠ືᛶࡢゎᯒ࠿ࡽࠊCO2྾╔࡟క࠺㓄఩Ꮚࡢ㐠ືᛶࡢపୗ࡟ࡼࡾࠊCO2ࡢᣑᩓ㏿ᗘࡢపୗࡀ⏕ࡌࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓࠋ[1]Materials and Methods
CID-Meࡣ᪤ሗ[2]࡟ᚑ࠸ྜᡂࡋࡓࠋ2H ᐃ⏝࡟㔜Ỉ⣲໬ࡋࡓbpyࢆ⏝࠸ࡓヨᩱࡶస〇ࡋࡓࠋᅛయ
㔠ᒓ–᭷ᶵᵓ㐀యࠊ࢞ࢫ྾╔ࢲ࢖ࢼ࣑ࢡࢫࠊ࣮ࣟࢱ࣮㓄఩Ꮚ‫ࢁࡦ࡜ࡶࡢࡎࡳࠊࢁࡦࡡࡴ࠸࠿ࡠ࠸ࠊࡸࡃࡓࡽࡣࡾࡃۑ‬－ 118 －NMR ᐃࡣ7 Tࡢ☢ሙ࡟࠾࠸࡚ࠊJEOL 4 mm HX MASࣉ࣮ࣟࣈࢆ
౑⏝ࡋ࡚⾜ࡗࡓࠋ࢞ࢫ㞺ᅖẼୗ࡟࠾ࡅࡿ
㛤Ⓨࡋࡓ㧗ᅽ࢞ࢫୗMASᐃࡢࡓࡵࠊᡃࠎࡀ௨๓

ᐃࢩࢫࢸ࣒[3]ࢆ࣮࣋ࢫ࡟ࠊJEOL 4 mm

ヨᩱ⟶࡜ྠᙧࡢࢪࣝࢥࢽ࢔〇ẼᐦMASヨᩱ⟶ࠊ࠾ࡼࡧᑓ⏝ࡢ࢞ࢫᑒධ⏝㓄⟶ࢆస〇ࡋ⏝࠸ࡓࠋヨᩱ⟶୰ࡢCO2ᅽຊࡣ0–1 MPa࡜ࡋࠊ
13

C

ᐃ᫬࡟ࡣ13C⃰⦰CO2࢞ࢫ (13C 99%) ࢆ౑⏝ࡋࡓࠋ

Results and Discussion
CID-Me୰࡟྾╔ࡋࡓCO2ࡢ13C MASࢫ࣌ࢡࢺࣝࢆFig. 2a࡟♧ࡍࠋᐃࡋࡓᅽຊ0.03–1 MPa (ྛcavity࡟CO2ࡀ1-2ಶ྾╔࡟┦ᙜ) ඲࡚࡟࠾࠸࡚ࠊ໬Ꮫࢩࣇࢺ␗᪉ᛶ (CSA) ࡟⏤᮶ࡍࡿࢧ࢖ࢻࣂࣥࢻࣃࢱ࣮ࣥࡀほࡉࢀࠊ྾╔࡟ࡼࡾCO2ࡢ㐠ືᛶࡀไ㝈ࡉࢀ࡚࠸ࡿࡇ࡜ࡀㄞࡳྲྀࢀࡿࠋCO2ࡀ⣽Ꮝ୰࡛

wobbling㐠ືࢆࡋ࡚࠸ࡿ࡜௬ᐃࡋࠊࢧ࢖ࢻࣂࣥࢻࣃࢱ࣮ࣥࡢࣇ࢕ࢵࢸ࢕ࣥࢢ࠿ࡽᚓࡓぢ࠿ࡅࡢ
CSA್ࡼࡾwobblingゅࡢᖹᆒ್ࢆồࡵࡓ࡜ࡇࢁࠊ྾╔㔞ࡢቑຍ࡟క࠸ゅᗘࡀ32°࠿ࡽ24°࡬࡜ῶᑡࡋ
ࡓࠋcavityෆࡢCO2ࡢᩘࡀቑ࠼ࡿࡇ࡜࡛❧య㞀ᐖࢆཷࡅࠊ㐠ືࡀไ㝈ࡉࢀࡓ࡜⪃࠼ࡽࢀࡿࠋࡇࡢ྾
╔ࡋࡓCO2࡟ࡼࡿ❧య㞀ᐖࡣࠊwindow㒊ࡢ㓄఩Ꮚbpyࡢᅇ㌿㐠ື࡟ࡶᙳ㡪ࡋᚓࡿ࡜⪃࠼ࠊ⥆࠸࡚0–
1 MPaࡢCO2ᅽຊୗ࡛2H

ᐃࢆ⾜࠸bpyࡢ㐠ື≧ែࢆゎᯒࡋࡓࠋbpyࡣ4-siteࣇࣜࢵࣉ㐠ືࢆࡋ࡚࠾

ࡾࠊ0࠾ࡼࡧ0.03 MPa (cavityෆࡢCO2ࡀ0࠾ࡼࡧ1ಶ)࡛ࡣࡑࡢ㏿ᗘࡣ106 Hz࡛࠶ࡗࡓࠋᅽຊࡀቑຍࡍ
ࡿ࡜㏿ᗘࡢ࣮࢜ࢲ࣮ࡀῶᑡࡋࠊ1 MPa (cavityෆࡢCO2ࡀ2ಶ)࡛ࡣ102 Hzࡲ࡛పୗࡋࡓࠋ྾╔ࡋࡓCO2
ࡀbpyࡢᅇ㌿㐠ື࡟ࡶᙳ㡪ࢆ୚࠼࡚࠸ࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋ
⣽Ꮝࡢwindow㒊ࡣbpyࡢᅇ㌿㐠ື࡟క࠸2.5-3.4 Ⴒࡢ⠊ᅖ࡛ኚ໬ࡋࠊCO2ศᏊࡢ኱ࡁࡉࡀ3.3 Ⴒ⛬ᗘ࡛࠶ࡿࡇ࡜࠿ࡽࠊbpyࡢ㐠ືࡸࡑࡢ㏿ᗘࡢኚ໬ࡣCO2ࡢ⣽Ꮝෆᣑᩓ࡟ᙳ㡪ࢆ୚࠼ࡿ࡜ண᝿ࡉࢀࡿࠋ
ࡑࡇ࡛ࠊ13C஺᥮NMR࡟ࡼࡿCID⤖ᬗෆࡢ྾╔CO2࡜CID⤖ᬗእࡢCO2࢞ࢫࡢ஺᥮㏿ᗘ࠿ࡽࠊᣑᩓ㏿ᗘࢆ᳨ウࡋࡓࠋ㠀ᖖ࡟㛗࠸ࢱ࢖࣒ࢫࢣ࣮ࣝࡢ஺᥮࡛࠶ࡗࡓࡓࡵࠊ0.03࠾ࡼࡧ1 MPa࡛13CO2ࢆ྾╔ࡉࡏࡓCID-Meࢆྠᅽຊࡢ㠀ྠ఩య⃰⦰CO2࢞ࢫୗ࡟୍ᐃ᫬㛫᫹ࡋࠊ஺᥮࡟ࡼࡗ࡚ῶᑡࡍࡿ13CO2ࡢಙྕᙉᗘࡢ᫬㛫ኚ໬ࢆゎᯒࡍࡿ࡜࠸࠺᪉ἲࢆ⏝࠸ࡓࠋᚓࡽࢀࡓ13Cಙྕࡢᙉᗘኚ໬࡟ᑐࡋ࡚exp᭤⥺࡛ࣇ࢕ࢵࢸ࢕ࣥࢢࢆ⾜࠸(Fig. 2b)ࠊ0.03 MPa࡛ࡣ3.510í4 Hzࠊ1
MPa࡛ࡣ7.010í5 Hz࡜࠸࠺஺᥮㏿ᗘࢆᚓࡓࠋᐇ㦂࡟⏝࠸ࡓヨᩱࡢ⤖ᬗࢧ࢖ࢬ࠿ࡽࠊᣑᩓಀᩘࡣ10í14 m2/s๓ᚋ࡜ィ⟬ࡉࢀࡓࠋࡇࢀࡣ
୍⯡ⓗ࡞MOF୰ࡢCO2ࡢᣑᩓಀᩘ10í8–10í10 m2/s࡜ẚ㍑ࡋ࡚㠀ᖖ࡟㐜࠸࡜ゝ࠼ࠊbpyࡢᅇ㌿࡟ࡼࡿ⣽Ꮝᚄኚ໬ࡀCO2ࡢᣑᩓ࡟ᙳ㡪ࢆ୚࠼࡚࠸ࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋbpyࡢᅇ㌿㏿ᗘࡀ኱ࡁࡃపୗࡍ
ࡿ1 MPa࡟࡚஺᥮㏿ᗘࡶపୗࡋࡓࡇ࡜ࡶࠊbpyࡢᅇ㌿࡜CO2ࡢᣑᩓࡀ࠶ࡿ⛬ᗘ༠ྠⓗ࡟㉳ࡁ࡚࠸ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ
௒ᅇࡢ⤖ᯝࡣ㓄఩Ꮚࡢ❧య㞀ᐖࡢຠᯝࡀ኱ࡁࡃ⌧ࢀࡿ⊃࠸⣽
ᏍࡢMOF࡛ᚓࡽࢀࡓࡶࡢࡔࡀࠊࡼࡾ኱ࡁ࡞⣽ᏍࡢMOF࡛ࡶ࢞ࢫ྾╔㔞ࡢቑ࠼ࡿ㧗ᅽୗ࡛ࡣࠊྠᵝࡢ⌧㇟࡟ࡼࡾ࢞ࢫศᏊࡢᣑᩓࡀ
㜼ᐖࡉࢀศ㞳⬟పୗ࡟ࡘ࡞ࡀࡿᜍࢀࡀ࠶ࡿࠋࡲࡓ㏫࡟ࠊ㓄఩Ꮚࡢᅇ㌿ࢆ฼⏝ࡋ࡚࢞ࢫศᏊࡢᣑᩓ㏿ᗘࢆไᚚ࡛ࡁࡿྍ⬟ᛶࢆ♧ࡍ⤖ᯝࡀᚓࡽࢀࡓ࡜⪃࠼ࡽࢀࡿࠋ
[1] T. Kurihara et al., J. Phys. Chem. Lett. 2022, 13, 7023.
[2] M. Inukai et al., Angew. Chem. Int. Ed. 2018, 57. 8687.
[3] M. Inukai et al., Phys. Chem. Chem. Phys. 2020, 22, 14465.

－ 119 －

L5-3

ᖖ☢ᛶ&H)ࡢࣇࢵ໬≀࢖࢜ࣥఏᑟࡢᅛయ105ゎᯒ‫ۑ‬ᮧୖ⨾࿴㸪ᕊ㔜

21ி㒔኱Ꮫ࣭⏘ᐁᏛ㐃ᦠᮏ㒊ࠊ2රᗜ┴❧኱Ꮫ኱Ꮫ㝔࣭ᕤᏛ◊✲⛉Solid-state NMR studies on fluoride-ion conduction pathways in paramagnetic CeF3
‫ۑ‬Miwa Murakami1, Atsushi Mineshige2
1

Office of Society-Academia Collaboration for Innovation, Kyoto University

2 Graduate School of Engineering, University of Hyogo

To unravel the ion conducting pathways among the three crystallographically inequivalent sites (F1, F2,
and F3) in CeF3, high-resolution MAS NMR spectra of 19F in CeF3 at -aÛ&DUHDQDO\]HGRQWKHEDVHV
RI WKH FDOFXODWHG GLSRODU FRXSOLQJ WHQVRU EHWZHHQ 19F and paramagnetic electron spins at Ce3+. Clearly
UHVROYHGVLGHEDQGPDQLIROGVIRU)a)DWÛ&LQGLFDWHWKDWLRQH[FKDQJHDPRQJWKHWKUHHVLWHVLVQRWIDVW
enough to affect the 19)VSHFWUXPZKHUHDV)PRWLRQLVVXJJHVWHGE\LWVEURDGHUOLQHZLGWK)XUWKHUZHVKRZ
that addition of only 0.1 % Sr2+ in CeF3 (Ce1-xSrxF3-x (x  EULQJVVLJQLILFDQWHIIHFWVRQ)-LRQPRELOLW\
While the F2 and the F3 manifolds DUH QRW DIIHFWHG E\ 6U-GRSLQJ DW  Û&, the F1 manifold is affected
DSSUHFLDEO\)XUWKHUDSDUWRIWKH)and most of the F3 manifolds are merged into the F1 signal DWÛ&.
7KHSUHIHUHQFHRIWKHH[FKDQJHSDWKZD\VLQ&H)3 is thus consistent with that postulated for LaF3, that is, F1)H[FKDQJHRFFXUVILUVWIROORZHGE\)-F3, and F1-)H[FKDQJHLVPRVWUHVWULFWHG㸯㸬┠ⓗࣇࢵ໬≀࢖࢜ࣥఏᑟయ࡜ࡋ࡚▱ࡽࢀࡿࢱ࢖ࢯࢼ࢖ࢺᆺCeF3ࡣࠊྂࡃ࠿ࡽNMR࡟ࡼࡿࢲ࢖ࢼ࣑ࢡ
ࢫ◊✲ࡀ⾜ࢃࢀ࡚࠸ࡿࡀࠊCe3+ࡢᖖ☢ᛶ࡟ࡼࡾ19F-NMRࢫ࣌ࢡࢺࣝࡢゎᯒࡣᅔ㞴࡛࠶ࡿࡓࡵࠊFࡢ㐠ືᛶ࡟㛵ࡋ࡚」ᩘࡢㄝࡀᥦၐࡉࢀ࡚࠸ࡓࠋᮏ◊✲࡛ࡣࠊࡲࡎࠊ☢ሙᙉᗘ㸭ヨᩱᅇ㌿㏿ᗘ㸭ᐃᗘࡢ㐺ษ࡞⤌ྜࡏࢆ㐺⏝ࡍࡿࡇ࡜࡟ࡼࡾࠊࢱ࢖ࢯࢼ࢖ࢺᆺᵓ㐀୰ࡢ3✀㢮ࡢFࢧ࢖ࢺF1(12g)ࠊ
F2(4d)ࠊF3(2a)ࡢಙྕࢆศ㞳ほ ࡋࠊḟ࡟ࠊᚓࡽࢀࡓ⥺ᙧࢆࠊ୙ᑐ㟁Ꮚ㸫19F᰾㛫ࡢ཮ᴟᏊ┦஫స⏝ࡸ໬Ꮫࢩࣇࢺࡢ␗᪉ᛶࢆྲྀࡾධࢀࡓ⥺ᙧࢩ࣑࣮ࣗࣞࢩ࡛ࣙࣥヲ⣽࡟ゎᯒࡍࡿࡇ࡜࡟ࡼࡾࠊྛFࢧ࢖
ࢺࡢᖐᒓࢆ☜❧ࡋࡓࠋࡉࡽ࡟ᑡ㔞Srࢆࢻ࣮ࣉࡋࡓヨᩱ࡟ࡘ࠸࡚ྠᵝࡢゎᯒ⾜࠺ࡇ࡜࡟ࡼࡾࠊྛFࢧ࢖ࢺ㛫ࡢ㐠ືᛶࡢ㐪࠸ࢆホ౯ࡋࡓࠋ㸰㸬ᐇ㦂ヨᩱࡣཎᩱࢆ࣮࣑࣎ࣝࣜࣥࢢ࡟ࡼࡾ⢊○࣭ΰྜᚋࠊ1000Υ࡛↝ᡂࡋ࡚స〇ࡋࡓࠋ 19F NMRࡣOpenCore NMRศගィ㸦4.7 T; 19Fࡢඹ㬆࿘Ἴᩘࡣ  0+]㸧ࢆ⏝࠸ࠊ ᐃ ᗘࡣ-40㹼240 Υࠊヨᩱᅇ㌿㏿ᗘࡣ23࠾ࡼࡧN+]࡛ ᐃࡋࡓࠋ㸱㸬⤖ᯝ࡜⪃ᐹFig.1࡟0$6  N+]࡛ᐃࡋࡓ0Υࡢ19F NMRࢫ࣌ࢡࢺࣝ࡜ࢩ࣑࣮ࣗࣞࢩࣙࣥ⤖ᯝࢆ♧ࡍࠋCeF3

ࡢNMR⥺ᙧࢆỴࡵࡿ᭱ࡶ኱ࡁ࡞┦஫స⏝ࡣ3౯ࡢࢭ࣒ࣜ࢘ࡢᖖ☢ᛶ㟁Ꮚ࡜19F᰾ࡢ཮ᴟᏊ┦஫స⏝
࡛࠶ࡾ1- 3ࠊ⤖ᬗᵓ㐀ࢆᇶ࡟ࠊ࡜࠶ࡿF࢖࢜ࣥ࠿ࡽ5 nm௨ෆࡢCe3+ࡢ୙ᑐ㟁Ꮚࢆ⪃࠼࡚␗᪉ᛶࢆィ⟬ࡋࡓࠋḟ࡟ᙳ㡪ࡀ኱ࡁ࠸ࡢࡣ19Fࡢ໬Ꮫࢩࣇࢺࡢ␗᪉ᛶ࡛࠶ࡿࡀࠊࡇࢀࡣィ⟬ࡢ㞴᫆ᗘࡀ㧗࠸ࡓࡵࠊࡇࡇ࡛ࡣࠊᐇ ࡢࢫ࣌ࢡࢺࣝ࡜ྜ࠺ࡼ࠺࡟⿵ṇ್࡜ࡋ࡚ධࢀࡓࠋ19F-19Fࡢ཮ᴟᏊ┦஫స⏝ࡣࠊ㧗㏿MAS࡟ࡼࡾ඘ศపῶ࡛ࡁ࡚࠸ࡿ࡜⪃࠼ࡓࠋ⤖ᬗᵓ㐀୰ࡢ⤌ᡂẚࢆ⏝࠸ࡓFig.1ୖࡢCeF3ࡢィ⟬ࢫ࣌ᖖ☢ᛶ┦஫స⏝㸪࢖࢜ࣥఏᑟయ㸪MAS⥺ᙧゎᯒ‫ࢃࡳࡳ࠿ࡽࡴۑ‬㸪ࡳࡡࡋࡆ࠶ࡘࡋ

－ 120 －

ࢡࢺࣝࡣᐇ ࢆࡼࡃ෌⌧ࡋ࡚࠾ࡾࠊF1㹼F3ࡢᖐᒓࢆ☜ᐃ࡛ࡁࡓࠋ100Υࡲ࡛ࡣࠊCSAࡀ ᗘኚ໬ࡋ࡞࠸࡜
ࡋ࡚ᐇࡢࢫ࣌ࢡࢺࣝࢆ෌⌧ࡍࡿࡇ࡜ࡀ࡛ࡁࡓࡇ

࡜࠿ࡽࠊ100Υ௨ୗ࡛ࡣFࡢ㐠ືࡀ㐜ࡃ⥺ᙧ࡟ᙳ㡪ࡋ࡞ ࠸ࡇ࡜ ࡀศ࠿ ࡗࡓࠋ Srࢆ 0.1%ࢻ࣮ࣉ ࡋࡓヨ ᩱ
㸦Fig.1ୗ㸧࡛ࡣࠊF2࡜F3ࡢ⥺ᙧ࡟ࡣኚ໬ࡣ࡞ࡃࠊF2
࡜F3ࡢ㐠ືࡀ↓ど࡛ࡁࡿ࡯࡝㐜࠸ࡇ࡜ࡀศ࠿ࡿࠋ୍
᪉ࠊF1ࡣ⥺ᙧኚ໬ࡀほ ࡉࢀࠊ㐠ື࡟ࡼࡿࡶࡢ࡜⪃࠼ࡓࠋFig.2࡟0$6N+]ࠊ240Υ࡛ ᐃࡋࡓCeF3࡜
x = 0.001ࡢヨᩱࡢࢫ࣌ࢡࢺࣝ࡜ࢩ࣑࣮ࣗࣞࢩࣙࣥ⤖ᯝࢆ♧ࡍࠋCeF3࡛ࡣࠊF1ಙྕࡢ┦ᑐᙉᗘࡀࢧ࢖ࢺࡢ
ẚࡼࡾᑠࡉࡃ࡞ࡗ࡚࠸ࡿࠋࡇࢀࡣF1ࡢ㐠ື࡟ࡼࡿࢫ
ࣆࣥࢫࣆࣥ⦆࿴᫬㛫ࡢῶᑡ࡛ㄝ࡛᫂ࡁࡿࠋx=0.001ヨFig. 1. 19F MAS NMR spectra of CeF3 andCe1-xSrxF3-x (x = 0.001) REVHUYHG at Û& (theࡾF1ࡢ⥺ᙧ⮬యࡀCeF3࡜ࡣ␗࡞ࡗ࡚࠸ࡿࠋࡲࡓࠊF3 EODFN OLQH . The individual calculatedࡢಙྕᙉᗘࡶF1࡜ࡢ஺᥮࡟ࡼࡾᑠࡉࡃ࡞ࡗ࡚࠸ࡿࠋ VSHFWUD DUH DOVR VKRZQ IRU ) EOXH longࡇࢀࡽࡢ⥺ᙧゎᯒ࠿ࡽࠊࡲࡎࠊF1㛫ࡢ஺᥮ࡀ㉳ࡇࡾࠊ dashed), F2 (green short-dashed), and F3(orange).
ᗘୖ࡛᪼F3ࡀ஺᥮࡟ཧຍࡋࠊ᭱ᚋ࡟F2ࡀཧຍࡍࡿ

ᩱ࡛ࡣࠊF1ྠኈࡢ஺᥮ࡸ␗࡞ࡿࢧ࢖ࢺ㛫ࡢ஺᥮࡟ࡼ

࡜࠸࠺ࡇ࡜ࡀ♧ࡉࢀࡓ4ࠋḟ࡟ࠊࣇࢵ໬≀࢖࢜ࣥࡢ㐠ືࢆヲ⣽࡟᳨ウࡍࡿࡓࡵ࡟ࠊ᭱ࡶ
㐠ືᛶࡀ㧗࠸F1࡟╔┠ࡋ࡚ࠊF1ࡢࡳࡀ㐠ື
ࡋ࡚࠸ࡿ0 Υ㸦Fig.1ୗ㸧࡛ゎᯒࢆ㐍ࡵࡓࠋF1
ࡢಙྕࡣᴟ➃࡟ᗈᖜ໬ࡋ࡚࠸ࡿࡇ࡜࠿ࡽࠊ
F1ࡢ㐠ືࡢ࿘Ἴᩘࡀ␗᪉ᛶࡢ3㹼10ಸ࡟࡞ࡗ࡚࠸ࡿ࡜᥎ᐃࡋࡓࠋࡑࡇ࡛ࠊ஺᥮㏿ᗘࡣ␗᪉ᛶࡢ5ಸ࡜⪃࠼࡚ࠊN+]࡜᥎ᐃࡋࡓࠋࡉ
ࡽ࡟ࠊ୍ᅇࡢ஺᥮࡛F1ࡀ᭱㏆᥋㊥㞳ࡔࡅ⛣ືࡍࡿ࡜ࡋ࡚ࠊᣑᩓಀᩘࢆồࡵ࡚ࠊNernstEinsteinᘧ࡜ᐇࡢఏᑟᗘࡢ್࠿ࡽ࢟ࣕࣜ

࢔ࠊࡘࡲࡾࠊF1ࡢ⃰ᗘࢆồࡵࡓ࡜ࡇࢁࠊ༢఩
⬊㎶ࡾ12ಶ࡜ᐇ㝿ࡢF1ࡢ⃰ᗘ࡜Ⰻࡃ୍⮴ࡍࡿ್ࢆᚓࡓࠋᚑࡗ࡚ࠊ0 Υ࡛ࡢ࢖࢜ࣥఏᑟࡣ

Fig. 2. Same DV)LJH[FHSWIRUWHPSHUDWXUH (Û&).

F1ࡢࡳ࡟ࡼࡿࡇ࡜ࢆ♧ࡍࡇ࡜ࡀ࡛ࡁࡓࠋ
References(1) A. Nayeem and J.P. Yesinowski, J. Chem. Phys. 89, 4600 (1988).
(2) F. Wang and C.P. Grey, Chem. Mater. 9, 1068 (1997).
(3) M. Murakami et al., J. Magn. Reson. 231, 66 (2013).
(4) M. Murakami and A. Mineshige, J. Phys. Chem. Solids 161, 110432 (2022).
ㅰ㎡㸸ࡇࡢᡂᯝࡣࠊᅜ❧◊✲㛤Ⓨἲே᪂࢚ࢿࣝࢠ࣮࣭⏘ᴗᢏ⾡⥲ྜ㛤Ⓨᶵᵓ㸦NEDO㸧ࡢጤク஦ᴗRISING2㸦JPNP16001㸧࠾ࡼࡧRISING3㸦JPNP21006㸧ࡢ⤖ᯝᚓࡽࢀࡓࡶࡢ࡛ࡍࠋ 4.7 Tࡢ☢ሙࡢ฼⏝ࡣࠊி㒔኱Ꮫ⌮Ꮫ㒊ࡢ➉⭜Ύ஀⌮ඛ⏕࡟ࡈ༠ຊ࠸ࡓࡔࡁࡲࡋࡓࠋ

－ 121 －

L5-4

ᅛయNMR࡟ࡼࡿ᭷ᶵELⓎගᮦᩱࡢᐃ㔞ⓗ㠀ᬗᵓ㐀ゎᯒ‫ۑ‬Ლᘯ඾ࠊ㕥ᮌඞ᫂
ி㒔኱Ꮫ࣭໬Ꮫ◊✲ᡤ

Quantitative amorphous structure analysis of organic light-emitting materials by solidstate NMR‫ۑ‬Hironori Kaji, Katsuaki Suzuki
Institute for Chemical Research, Kyoto University
In recent years, thermally activated delayed fluorescence (TADF) materials have attracted significant
attention as a new type of emitter in organic light-emitting diodes (OLEDs). This is because TADF canconvert originally dark triplet excitons into light through reverse intersystem crossing (RISC). TADF
molecules have donor-acceptor (D-A) structures to allow the RISC process, and the torsion angle between
the D and A segments is extremely important for the TADF performance. However, the torsion angle between
the D and A units has not been analyzed in detail because organic materials in OLEDs are in an amorphousstate. Here, we analyzed the torsion angle of DACT-II, a representative of excellent TADF molecules, in theamorphous state by solid-state heteronuclear multiple-quantum correlation (HMQC) NMR experiment. The
experimentally-obtained HMQC spectrum was well reproduced by a simulated one with widely distributed
torsion angles.
⌧ᅾࠊᡃࠎࡣࠕ᭷ᶵⓎගᮦᩱ࠾ࡼࡧࢹࣂ࢖ࢫࡢࣁ࢖ࢫ࣮ࣝࣉࢵࢺ㛤Ⓨࠖ[1,2]ࠊࠕ᭷ᶵⓎගᮦᩱࡢ⢭ᐦ㔞Ꮚ໬Ꮫィ⟬ࠖ[3]ࠊ
ࠕ㟁Ⲵ㍺㏦࣐ࣝࢳࢫࢣ࣮ࣝࢩ࣑࣮ࣗࣞࢩࣙࣥࠖ[4]ࠊ
ࠕ᭷ᶵELࡢNMRゎᯒࠖ
[5-7]ࠊࡢ4ࡘࢆᰕ࡜ࡋ࡚ࠊ᭷ᶵEL࡟㛵ࡍࡿ◊✲ࢆ㐍ࡵ࡚࠸ࡿࠋ௒ᅇࠊᡃࠎࡀタィࡋࡓ᭷ᶵELⓎගᮦᩱ࡛࠶ࡿDACT-II (ᅗ1) [1] ࡟ᑐࡋࠊᅛయNMR࡟ࡼࡿ⢭ᐦゎᯒࢆ⾜ࡗࡓࠋ࠙⇕άᛶ໬㐜ᘏ⺯ග (TADF)ᮦ
ᮦᩱࡢタィ࡜㛤Ⓨࠚ᭷ᶵELࡣ㟁ὶὀධ࡟ࡼࡾගࢆᚓࡿࢹࣂ࢖ࢫ࡛࠶ࡿࠋ୧㟁ᴟ࠿ࡽ࣮࣍ࣝ࡜㟁ᏊࡀὀධࡉࢀࠊⓎගᒙ࡟࠾࠸࡚ࡑࢀࡽࡀ෌⤖ྜࡍࡿࡇ࡜࡟ࡼࡾບ㉳Ꮚࡀ⏕ᡂࡍࡿࠋࡇࡢ
᫬ࠊ୍㔜㡯ບ㉳Ꮚ (S1) ࡜୕㔜㡯ບ㉳Ꮚ (T1) ࡀ 25% : 75%ࡢẚ⋡࡛⏕ᡂࡍࡿࡀࠊᚑ᮶ࡢ⺯ගᮦᩱࢆ⏝࠸ࡓࢹࣂ࢖ࢫ࡛ࡣࠊT1ࡣ⇕࡜ࡋ࡚ኻάࡋ
࡚ࡋࡲ࠺ࡓࡵࠊ඲ບ㉳Ꮚࡢ࠺ࡕ᭱኱࡛ࡶ25%ࡋ࠿ග࡟ኚ᥮ࡍࡿࡇ࡜ࡀ࡛
ࡁ࡞࠿ࡗࡓࠋࡋ࠿ࡋࠊS1㸫T1 㛫ࡢ࢚ࢿࣝࢠ࣮ᕪ (ǻEST) ࢆᑠࡉࡃࡍࡿࡇ
࡜࡟ࡼࡾࠊᐊ ࡛ࡢ⇕࢚ࢿࣝࢠ࣮࡛ T1 ࠿ࡽ S1 ࡬ࡢ࠸ࢃࡺࡿ㏫㡯㛫஺ᕪ (RISC) ࡀྍ⬟࡟࡞ࡿ࡜ண᝿ࡉࢀࠊᐇ㝿࡟ࡑࡢ⌧㇟࡟ᇶ࡙ࡃࠊTADF

Fig. 1. Structure of
DACT-II.
Doublelabel is only for࡟ࡼࡿບ㉳Ꮚࢆ100%ග࡟ኚ᥮ࡍࡿࡇ࡜ࡀᐇ㦂ⓗ࡟ࡶ♧ࡉࢀ[1]ࠊ⌧ᅾࠊ
NMR
measurements.
TADF࡟㛵ࡍࡿᮦᩱ㛤Ⓨࠊᇶ♏◊✲ࡀୡ⏺୰࡛άⓎ࡟࡞ࡗ࡚࠸ࡿࠋ

࡜ࡼࡤࢀࡿⓎගᮦᩱࡀ㛤Ⓨࡉࢀࡓ[8]ࠋᅗ1ࡢDACT-II࡟ࡼࡾࠊ㟁ὶບ㉳

࠙ᅛయHMQC ᐃ࡟ࡼࡿ㠀ᬗᵓ㐀ゎᯒࠚᚑ᮶ࠊ᭷ᶵ≀㉁࡟࠾࠸࡚ࡣ୙ྍ⬟࡛࠶ࡗࡓࡇࡢRISCࢆᐇ⌧ࡍࡿࡓࡵ࡟ࡣࠊୖ㏙ࡢ㏻ࡾࠊǻESTࢆ࡛ࡁࡿࡔࡅᑠࡉࡃࡍࡿᚲせࡀ࠶ࡿࠋǻESTࡣࠊศᏊ࡟࠾ࡅࡿ
HOMO࡜LUMOࢆ✵㛫ⓗ࡟ศ㞳ࡍࡿࡇ࡜࡟ࠊࡼࡾᑠࡉࡃ࡛ࡁࡿࡇ࡜ࡀ⌮ㄽⓗ࡟᫂ࡽ࠿࡜࡞ࡗ࡚࠾
᭷ᶵEL, Ⓨග, ᅛయHMQC‫ࡾࡢࢁࡦࡌ࠿ۑ‬㸪ࡍࡎࡁ࠿ࡘ࠶ࡁ

－ 122 －ࡾࠊTADFศᏊࡣ㟁Ꮚࢻࢼ࣮ᛶࢭࢢ࣓ࣥࢺ(D)࡜࢔ࢡࢭࣉࢱ࣮ᛶࢭࢢ࣓ࣥࢺ(A)ࢆ⤖ྜࡉࡏࡿࡇ࡜࡟ࡼࡾタィࡉࢀ࡚ࡁࡓࠋᅗ1࡟♧
ࡍ㏻ࡾࠊDACT-IIࡶࡑࡢᵓ㐀ࢆ᭷ࡋ࡚࠸ࡿࠋ
ࡇࡢD-A⤖ྜᆺศᏊ࡟࠾࠸࡚ࡣࠊD࡜Aࢆ⧅࠸࡛࠸ࡿ⤖ྜࡢࡡࡌࢀゅ(ᅗ1ࡢȕ)ࡣHOMO
࡜LUMOࡢ㔜࡞ࡾ࡟ᙳ㡪ࡋࠊǻESTࢆ኱ࡁࡃኚ໬ࡉࡏࡿࠋȕࡣࠊࢫࣆࣥ㌶㐨┦஫స⏝ࠊ᣺ືᏊᙉᗘࠊS1ࡢ࢚ࢿࣝࢠ࣮‽఩࡟ࡶᙳ㡪ࡍ
ࡿࡓࡵࠊRISC࡟࠾ࡅࡿࢫࣆࣥ཯㌿ࠊ㍽ᑕ⦆࿴ࠊⓎගⰍ࡟ࡶኚ໬ࢆࡶࡓࡽࡍࠋࡑࡢࡓࡵࠊ
ࡇࡢȕࢆᐃ㔞ⓗ࡟ゎᯒࡍࡿࡇ࡜ࡣࠊTADFศ
Ꮚ࠾ࡼࡧࢹࣂ࢖ࢫ≉ᛶࡢ⌮ゎ࡟ᴟࡵ࡚㔜せ࡛࠶ࡿࠋࡋ࠿ࡋࡑࡢ୍᪉࡛ࠊ᭷ᶵᮦᩱࡣࢹࣂ Fig. 2. Simulated HMQC spectra of 13C/2H-DACT-II.
࢖ࢫ୰࡛㠀ᬗ≧ែ࡟࠶ࡿࡓࡵࠊࡑࡢゎᯒࡣᅔ㞴࡞≧ἣ࡟࠶ࡿࠋᮏ◊✲࡛ࡣࠊᅗ1࡟♧ࡋࡓ13C࡜2Hࢆࢲࣈࣝࣛ࣋ࣝࡋࡓDACT-IIࡢ㠀ᬗヨᩱ࡟ᑐࡋࠊᅛయ13C-2H HMQC ᐃࢆ⾜ࡗࡓࠋࡇࡢ ᐃ࡛ࡣࠊࣛ࣋ࣝ㒊఩㛫ࡢ㓄ྥ┦㛵ࠊࡋࡓࡀࡗ࡚ࠊࡑࡢ
㛫ࡢࡡࡌࢀゅࢆศᕸࡶྵࡵ࡚ゎᯒࡍࡿࡇ࡜ࡀྍ⬟࡛࠶ࡿ[9]ࠋᅗ2࡟13C/2H-DACT-IIࡢHMQCࢩ࣑ࣗ
࣮ࣞࢩࣙࣥࢫ࣌ࢡࢺࣝࢆ♧ࡍࠋࡡࡌࢀゅࡢኚ໬࡟ࡼࡾࢫ࣌ࢡࢺࣝࡀ኱ࡁࡃኚ໬ࡋࠊ⢭ᗘࡢ㧗࠸ゎᯒࡀྍ⬟࡛࠶ࡿࡇ࡜ࡀࢃ࠿ࡿࠋᅗ3a࡟ࡣࠊᐇ ࢫ࣌ࢡࢺࣝࢆ♧ࡍࠋࡇࡢࢫ࣌ࢡࢺࣝࡣࠊ༢୍ࡢȕ࡛ࡣ෌⌧࡛ࡁࡎࠊᅗ3b࡟♧ࡋࡓ᭱㐺ࣇ࢕ࢵࢺ࠿ࡽࠊD-A㛫ࡢࡡࡌࢀゅࡣࠊᅗ3cࡢゅᗘศᕸࢆ᭷ࡍࡿࡇ
࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓࠋ
ㅰ㎡㸸ᮏ◊✲ࡣࠊJSPS⛉◊㈝ JP20H05840 (Ꮫ⾡ኚ㠉㡿ᇦ◊✲ࠕືⓗ࢚࢟ࢩࢺࣥࠖ)ࠊCore-to-Coreࣉࣟࢢ࣒ࣛ࡟ࡼࡾຓᡂࡉࢀࡓࠋ

Fig. 3. Experimental and best fit simulated MQC spectra of 13C/2H-DACT-II.
References[1] H. Kaji, H. Suzuki, T. Fukushima, K. Shizu, K. Suzuki, S. Kubo, T. Komino, H. Oiwa, F. Suzuki, A. Wakamiya,
Y. Murata, C. Adachi, Nat. Commun. 2015, 6, 8476.
[2] Y. Wada, H. Nakagawa, S. Matsumoto, Y. Wakisaka, H. Kaji, Nat. Photon. 2020, 14, 643.
[3] K. Shizu, H. Kaji, Commun. Chem. 2022, 5, 53.
[4] S. Kubo, H. Kaji, Sci. Rep. 2018, 8, 13462.
[5] F. Suzuki, T. Fukushima, M. Fukuchi, H. Kaji, J. Phys. Chem. C 2013, 117, 18809.
[6] T. Fukushima, J. Yamamoto, M. Fukuchi, S. Hirata, H. H. Jung, O. Hirata, Y. Shibano, C. Adachi, H. Kaji, AIP
Advances 2015, 5, 087124.
[7] K. Suzuki, S. Kubo, F. Aussenac, F. Engelke, T. Fukushima, H. Kaji, Angew. Chem. Int. Ed. 2017, 56, 14842.
[8] H. Uoyama, K. Goushi, K. Shizu, H. Nomura, C. Adachi, Nature 2012, 492, 234.
[9] H. Kaji, K. Schmidt-Rohr, Macromolecules 2001, 34, 7382.

－ 123 －

L5-5ᐃ୰࡟ࣃ࣓࣮ࣛࢱࢆ⮬ᚊⓗ࡟㑅ᢥࡍࡿࡇ࡜࡛㧗⢭ᗘࢆ┠ᣦࡍ㐺ᛂⓗNMR ᐃἲ‫ⴱۑ‬す༟☻ࠊᮌᕝ㝯๎11⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮An adaptive method for high-precision NMR by autonomously selecting experimental
parameters during the measurement‫ۑ‬Takuma Kasai1, Takanori Kigawa1
1

RIKEN Center for Biosystems Dynamics Research
NMR analyses of challenging samples are often obstructed by insufficient sensitivity. Optimization of theexperimental parameters may improve precision of the analyses; however, the optimization itself may bedifficult in such cases. Here we propose an adaptive method to optimize the experimental parameters during
the measurement, applied for chemical exchange saturation transfer (CEST) as an example. In conventional
CEST experiments under high-sensitivity situations, it is usual to utilize equally spaced irradiation offsets,most of which are redundant for the estimation of the exchange parameters. On the contrary, in the proposed
method, the machine resource is devoted to experimental conditions with higher information content. To
achieve this, we developed an iterative procedure with Bayesian inference. Within each iteration, we firstly
estimate prior probability of the parameters using the data observed so far. Secondly, expected information
gain is calculated for each experimental condition candidate. Finally, the best condition is selected for the
next measurement. Since it can also be applied to various types of experiments, we believe this strategy
should expand targets and application areas of NMR.
NMRࡣศᏊࡢࡉࡲࡊࡲ࡞≉ᛶࢆゎᯒ࡛ࡁࡿ᪉ἲ࡛࠶ࡿࡀࠊᑐ㇟ศᏊࡢ≀⌮ⓗᛶ㉁࡟ࡼࡗ࡚⃰ᗘࢆୖࡆࡿࡇ࡜ࡀ࡛ࡁ࡞࠿ࡗࡓࡾࠊಙྕࡀࣈ࣮ࣟࢻ࡛࠶ࡗࡓࡾ࡞࡝ࡢ⌮⏤࡛NMRࢫ࣌ࢡࢺࣝࡢឤᗘ
ࡀప࠸ሙྜ࡟ࡣࠊゎᯒ⤖ᯝࡢ⢭ᗘࡀ㝈ࡽࢀࡿࠋࡇࡢࡼ࠺࡞ሙྜࠊNMR ᐃࣃ࣓࣮ࣛࢱࡢ᭱㐺໬࡟ࡼࡾᐃࢹ࣮ࢱࡢ㉁ࢆྥୖࡉࡏࠊゎᯒ⤖ᯝࢆᨵၿࡍࡿࡇ࡜ࡀᮃࡲࢀࡿࠋࡋ࠿ࡋࠊࡑࡢ᭱㐺໬ࡢࡓࡵࡢᐃࡀᅔ㞴࡛࠶ࡗࡓࡾࠊ

ᐃࢆጞࡵ࡚ࡳ࡞࠸࡜᭱㐺໬ࡢࡓࡵࡢ᝟ሗࡀᚓࡽࢀ࡞࠿ࡗࡓࡾࡍࡿ

ሙྜ࡟ࡣࠊ ᐃ୰࡟ࣃ࣓࣮ࣛࢱ᭱㐺໬ࢆ࠾ࡇ࡞࠺ࠕ㐺ᛂⓗNMR ᐃࠖࡀ᭷ຠ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ
๓⪅ࡢ౛࡜ࡋ࡚ࠊឤᗘࡢప࠸1ḟඖNMRᐃ୰࡟⦪⦆࿴᫬ᐃᩘT1ࡢ᝟ሗࢆྜࢃࡏ࡚ྲྀᚓࡋບ㉳ゅࢆ᭱㐺໬ࡍࡿ᪉ἲࢆ᫖ᖺሗ࿌ࡋࡓ1ࠋᚋ⪅ࡢ౛࡜ࡋ࡚ࠊ༨ࡵࡿ๭ྜࡀᑠࡉ࠸ࡓࡵ࡟┤᥋ほ ࡛ࡁ࡞࠸ศᏊ≧ែ㸦௨ୗࠕB≧ែࠖ࡜࠸࠺㸧࡜ࡢ໬Ꮫ஺᥮ࢆࠊከᩘࢆ༨ࡵࡿ≧ែ㸦௨ୗࠕA≧ែࠖ࡜࠸࠺㸧ࡢศᏊࢆ㏻ࡌ࡚ほ ࡍࡿᡭἲ࡛࠶ࡿ
chemical exchange saturation transfer (CEST)ἲࡀᣲࡆࡽࢀࡿࠋᚑ᮶ᆺࡢCESTἲ࡛ࡣࠊ㏻ᖖࠊ࿘Ἴᩘ
࢜ࣇࢭࢵࢺࢆᩘ༑Ⅼ࡟ࢃࡓࡗ୍࡚ᐃࡢ㛫㝸࡛ኚ࠼࡞ࡀࡽᙅ࠸ᦤືࣃࣝࢫࢆ↷ᑕࡋ㸦Fig.1ୖ㸧ࠊA≧
ែࡢඹ㬆ࢆほほࡍࡿࠋA≧ែࡢ໬Ꮫࢩࣇࢺࡔࡅ࡛࡞ࡃࠊB≧ែࡢ໬Ꮫࢩࣇࢺ࡛↷ᑕࡋࡓሙྜ࡟ࡶࠊ

ࡉࢀࡿಙྕᙉᗘࡢపୗࡀ࠶ࡾ㸦Fig.1ୖ㸧ࠊࡇࡢࡇ࡜ࡀB≧ែࡢᏑᅾࢆド᫂ࡍࡿࠋࡲࡓࠊ࿘Ἴᩘ

࡟ᑐࡍࡿᙉᗘࡢᛂ⟅ࢆ⌮ㄽᘧ࡟࠶࡚ࡣࡵࡿࡇ࡜࡛ࠊB≧ែࡢᏑᅾ๭ྜࡸࠊ஺᥮㏿ᗘ➼ࡢ᝟ሗࢆᚓࡿ
ࡇ࡜ࡀ࡛ࡁࡿࠋࡇࡢ࡜ࡁࠊA࣭B୧≧ែࡢ໬Ꮫࢩࣇࢺ࠿ࡽ㐲࠸࿘Ἴᩘࡢほ Ⅼࡣࠊ໬Ꮫ஺᥮࡟㛵ࡍࡿ᝟ሗࢆࡶࡗ࡚࠾ࡽࡎࠊ ᐃࡍࡿᚲせᛶࡣప࠸ࠋឤᗘࡀ༑ศ࡞ሙྜࡣࡇࡢ᪉ἲ࡛Ⰻ࠸ࡀࠊឤᗘࡀ
ᐃࣃ࣓࣮ࣛࢱ᭱㐺໬ࠊ࣋࢖ࢬ᥎ᐃࠊ᝟ሗ⌮ㄽ‫ࡾࡢ࠿ࡓ ࢃࡀࡁࠊࡲࡃࡓ ࠸ࡉ࠿ۑ‬－ 124 －

ప࠸ሙྜ࡟ࡣࠊᚑ᮶ᆺCESTࡢࡼ࠺࡟ࠊ࠶ࡽࡺࡿ࿘Ἴᩘ࡟ ᐃ㈨※ࢆᆒ୍࡟ᢞධࡋ࡚ ᐃࡍࡿࡼࡾࡶ㸦Fig.1୰㸧ࠊA࣭B୧≧ែࡢ໬Ꮫࢩࣇࢺࡢ㏆ഐ࡞࡝ࠊ໬Ꮫ஺᥮࡟㛵ࡍࡿ᝟ሗࢆࡼࡾከ
ࡃࡶࡘほ Ⅼ࡟㞟୰ⓗ࡟ ᐃ㈨※ࢆᢞධࡋࠊ✚⟬ᅇᩘࢆቑࡸ
ࡋࡓ࡯࠺ࡀ㸦Fig.1ୗ㸧ࠊ┠ⓗ࡜ࡍࡿ໬Ꮫ஺᥮ࣃ࣓࣮ࣛࢱࢆ᭱
⤊ⓗ࡟⢭ᗘࡼࡃồࡵࡿࡇ࡜ࡀ࡛ࡁࡿ࡜ᛮࢃࢀࡿࠋB≧ែࡢ໬Ꮫࢩࣇࢺࢆᐃ๓࡟▱ࡿࡇ࡜ࡣ࡛ࡁ࡞࠸ࡢ࡛ࠊ࡝ࡢࡼ࠺࡞ほⅬ࡟ ᐃ㈨※ࢆᢞධࡍ࡭ࡁ࠿ࡣ ᐃ㛤ጞᚋ࡟Ỵࡵࡿࠋ ࡛ࡣࠊ࡝ࡢࡼ࠺࡞ᇶ‽࡟ᇶ࡙࠸࡚ほ Ⅼࢆ㑅ᢥࡋࡓࡽࡼ࠸
ࡔࢁ࠺࠿ࠋᚑ᮶ᆺࡢCEST ᐃ࡛ࡣࠊᩘ༑Ⅼࡢほ Ⅼ㸦࢜ࣇࢭࢵࢺ㸧ࢆࡍ࡭࡚1ᅇࡎࡘ ᐃࡍࡿ࡜࠶ࡽ࠿ࡌࡵỴࡵ࡚ᐃࢆ㛤ጞࡋࠊ㛤ጞᚋ࡟ ᐃ᮲௳ࢆኚ᭦ࡍࡿࡇ࡜ࡣ࡞࠸ࠋ㐺ᛂⓗCEST
ᐃ࡛ࡣࠊ1ᅇ ᐃࡍࡿࡈ࡜࡟ࡑࢀࡲ࡛ࡢࢹ࣮ࢱ࡟ࡶ࡜࡙࠸࡚
ḟࡢほ ⅬࢆỴࡵࡿࠊiterative࡞᪉ἲࡀࡼ࠸࡜ᛮࢃࢀࡿࠋࡲࡓࠊ
ឤᗘࡀᝏ࠸ሙྜ࡟ࡣࠊ᭱ࡶᙜ࡚ࡣࡲࡾࡢࡼ࠸ࣃ࣓࣮ࣛࢱࡢࡳ
ࢆồࡵࡿⅬ᥎ᐃࡼࡾࡶࠊࣃ࣓࣮ࣛࢱࡢ☜⋡ศᕸࢆồࡵࡿ࣋࢖ࢬ᥎ᐃࡢ࡯࠺ࡀࠊࣃ࣓࣮ࣛࢱࡢ᥎ᐃ⢭ᗘࡶ▱ࡿࡇ࡜ࡀ࡛ࡁ࡚

Fig. 1. Conventional and adaptive
CEST experiments.

ࡼ࠸ࠋᥦ᱌ἲ࡛ࡣࠊiterationࡈ࡜࡟ࠊࡑࢀࡲ࡛࡟ほ ࡋࡓࢹ࣮ࢱ࠿ࡽࣃ࣓࣮ࣛࢱࡢ☜⋡ศᕸ‫݌‬ሺદሻࢆ࣐ࣝࢥࣇ㐃㙐ࣔࣥࢸ࢝ࣝࣟ(MCMC)ἲ࡟ࡼࡾ࣋࢖ࢬ᥎ᐃࡍࡿࠋ௬࡟ほ Ⅼ࢞ࢆ㑅ࢇࡔ࡜ࡁ࡟ ᐃ್෡ࡀᚓࡽࢀࡿ࡜ࡍࡿ࡜ࠊ஦ᚋ☜⋡ศᕸࡣ‫݌‬൫દȁ‫܇‬෡൯࡜࡞ࡿࠋ‫܇‬෡ࡢほ ࡟ࡼࡾᚓࡽࢀࡿ▱㆑ࢆࠊ2ࡘࡢ☜⋡‫܇‬෡൯ȁȁ‫݌‬ሺદሻሻ࡛ぢ✚ࡶࡿࡇศᕸࡢᕪ␗ࢆ࠶ࡽࢃࡍᣦᶆ࡛࠶ࡿ࢝ࣝࣂࢵࢡ࣭ࣛ࢖ࣈ࣮ࣛ᝟ሗ㔞‫ ୐୏ܦ‬ሺ‫݌‬൫દȁ‫܇‬෡ࡣᑗ᮶ࡢほ ್࡛࠶ࡿࡓࡵࠊ‫܇‬෡࡟ࡘ࡜࡜ࡍࡿࠋ‫܇‬෡൯ȁȁ‫݌‬ሺદሻሻ൧
࠸࡚ᮇᚅ್ࢆ࡜ࡗࡓ㔞ॱ‫܇‬෡ ൣ‫ ୐୏ܦ‬ሺ‫݌‬൫દȁ‫܇‬ࡀࠊほ Ⅼ࢞ࢆ㑅ࢇࡔ᫬࡟ᚓࡽࢀࡿ▱㆑ࡢᮇᚅ್࡜࠸࠺ࡇ࡜࡟࡞ࡿࠋࡇࡢ㔞ࡣ┦஫᝟ሗ㔞෡൯Ǣ ‫݌‬ሺદሻቁ࡟➼ࡋࡃࠊ஦๓☜⋡ศᕸ‫݌‬ሺદሻ࠿‫ ܫ‬ቀ‫݌‬൫‫܇‬
ࡽࡢMCMCࢧࣥࣉࣝࢆ⏝࠸࡚ィ⟬࡛ࡁࡿࠋࡇ
ࡢࡼ࠺࡞࢔ࣝࢦࣜࢬ࣒࡟ࡼࡾࠊiterationࡈ࡜࡟ࠊḟ࡟᭱ࡶከࡃࡢ▱㆑ࢆ⋓ᚓ࡛ࡁࡑ࠺࡞ほⅬࢆ㑅ࡧࠊ ᐃࢆ㐍ࡵ࡚࠸ࡃࠋ
 Fig.2࡟ᥦ᱌ἲࡢࢥࣥࣆ࣮ࣗࢱࢩ࣑࣮ࣗࣞࢩ
ࣙࣥࡢ୍౛ࢆ♧ࡍࠋiterationࡀ㐍ࡴ࡟ࡘࢀ࡚ࠊ᭱
኱஦ᚋ☜⋡(maximum-a-posteriori; MAP)᥎ᐃ್
ࡀṇゎ࡟㏆࡙ࡁࠊಙ⏝༊㛫ࡶ⊃ࡃ࡞ࡿࡇ࡜࠿
ࡽࠊ໬Ꮫ஺᥮ࣃ࣓࣮ࣛࢱࡢ᥎ᐃ⢭ᗘ࣭☜ᗘࡀୖࡀࡗ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡿࠋㅮ₇࡛ࡣࠊࢩ࣑ࣗࣞ
࣮ࢩࣙࣥ࠾ࡼࡧᐇ ࢹ࣮ࢱ࡟ࡼࡾࠊࣃ࣓࣮ࣛࢱ
᥎ᐃ⢭ᗘ࣭☜ᗘࢆᚑ᮶ᆺCEST࡜ẚ㍑ࡍࡿࠋ

Fig. 2. An example of simulated adaptive CEST.

Reference(1) T. Kasai and T. Kigawa (2021), “In-measurement T1 estimation for adaptive optimization of the excitation
angles and the recycling delays to improve NMR sensitivity”, ISMAR-APNMR-NMRSJ-SEST2021, Osaka,
Japan.

－ 125 －

L5-6

⏕యヨᩱࡢ༟ୖNMR⿦⨨࡟ࡼࡿศᯒᡭἲࡢ᳨ウż┦ἑᬛᗣ1㸪ᏵᏊ㇦1㸪⏑Ⳁ1㸪ⵓె⛥1㸪⬌▱ᙪ1㸪኱す⿱Ꮨ1㸪㛗⏣ㄔྖ2㸪ஂ⡿⏣༤அ1㸪⇃ᮌᗣ⿱1㸪ᒣෆ୍ኵ31໭ᾏ㐨኱Ꮫ࣭኱Ꮫ㝔ඛ➃⏕࿨⛉Ꮫ◊✲㝔
2୰ᒣၟ஦ᰴᘧ఍♫3Ἀ⦖⛉Ꮫᢏ⾡኱Ꮫ㝔኱Ꮫ ᶵჾศᯒࢭࢡࢩࣙࣥ

Study of analysis techniques using benchtop NMR for biological samplesżTomoyasu Aizawa1, Zihao Song1, Li Gan1, Jiaxi Jiang1, Zhiyan Hu1, Yuki Ohnishi1, Seiji Osada2,
Hiroyuki Kumeta1, Yasuhiro Kumaki1, Kazuo Yamauchi3
1 Faculty of advanced life science, Hokkaido university
2

Nakayama Co.,Ltd.

3 Instrumental analysis section, Okinawa institute of science and technology

Superconducting high-field nuclear magnetic resonance (NMR) is one of the leading methods inmetabolomics. It is increasingly attracting attention because of its ability to obtain highly reproducible datawith simple sample preparation. However, compared to its use in the research field, its use in clinical testing
and the food industry has remained limited. This is partly due to the high cost of high-field NMR systems
and the high hurdles in accessing the systems themselves. In this presentation, we report the results of analysisof oligosaccharides in human breast milk and metabolites in stools of DSS enteritis model mice as a basic
study of NMR metabolome analysis using a bench-top NMR system, which is becoming increasingly
sophisticated.
ࠕపศᏊ௦ㅰ≀㸦࣓ࢱ࣎ࣛ࢖ࢺ㸧ࠖࢆ⥙⨶ⓗ࡟ゎᯒࡍࡿ࣓ࢱ࣑࣎ࣟࢡࢫ㸦࣓ࢱ࣮࣒࣎ࣟゎᯒ㸧ࡣ⑌⑓ࡢཎᅉศᯒ➼ࡢ་Ꮫศ㔝࡛ࡢ◊✲ࡸᢏ⾡㛤Ⓨࢆ୰ᚰ࡟㐍ᒎࡋ࡚ࡁࡓࠋ㏆ᖺ࡛ࡣࠊ」㞧࡞⤌ᡂࢆᣢࡘ㎰ᯘỈ⏘≀࣭㣗ရࡢᡂศศᯒ➼ࡢ⏘ᴗศ㔝࡬ࡢᛂ⏝◊✲ࡶቑຍࡋ࡚࠸ࡿࠋ㉸ఏᑟ㧗☢ሙ᰾☢Ẽඹ㬆㸦NMR㸧⿦⨨ࢆ⏝࠸ࡓゎᯒࡣࠊ௦⾲ⓗ࡞࣓ࢱ࣑࣎ࣟࢡࢫᡭἲࡢ1ࡘ࡛࠶ࡾࠊᐜ᫆࡞ヨᩱㄪ〇࡛෌⌧ᛶࡢ㧗࠸ࢹ࣮ࢱࡀᚓࡽࢀࡿࡇ࡜࡞࡝࠿ࡽࠊࡲࡍࡲࡍ⬮ගࢆᾎࡧ࡚࠸ࡿࠋࡋ࠿ࡋ࡞ࡀࡽࠊ
◊✲ศ㔝࡛ࡢ฼⏝࡜ẚ㍑ࡋ࡚ࠊ⮫ᗋ᳨ᰝࡸ㎰ᯘỈ⏘࣭㣗ရ⏘ᴗศ㔝࡬ࡢᛂ⏝ࡣࠊࡲࡔ㝈ᐃⓗ࡟࡜࡝ࡲࡗ࡚࠸ࡿࠋࡇࢀࡣࠊ㧗☢ሙNMR⿦⨨ࡣ㧗㢠࡛࠶ࡾࠊ㉸ఏᑟ⥔ᣢࡢࡓࡵࡢᾮయ࣒࣊ࣜ࢘➼ࡢ෭፹ࡢ౪⤥࡞࡝ࡢ⟶⌮సᴗࡀᚲ㡲࡛ࠊ⿦⨨ࡑࡢࡶࡢ࡬ࡢ࢔ࢡࢭࢫࡢࣁ࣮ࢻࣝࡀ㧗࠸ࡇ࡜ࡶ୍ᅉ࡛࠶
ࡿ࡜⪃࠼ࡽࢀࡿࠋ
ࡑࡇ࡛ᡃࠎࡣࠊ㏆ᖺᛴ⃭࡟㧗ᛶ⬟໬ࡀ㐍ࡴ༟ୖNMR⿦⨨ࢆ฼⏝ࡋࠊNMR࣓ࢱ࣑࣎ࣟࢡࢫゎᯒࢆ⾜࠺࡜࠸࠺ㄢ㢟࡟ྲྀࡾ⤌ࢇ࡛࠸ࡿࠋ༟ୖNMR⿦⨨ࡣᙉຊ࡞ࣞ࢔࢔࣮ࢫỌஂ☢▼ࡢ฼⏝ࡸࠊ㧗ᗘ࡞㟁Ꮚไᚚ࡜࠸ࡗࡓ᭱᪂ᢏ⾡ࡢᑟධ➼࡟ࡼࡾࠊᛴ⃭࡟㧗ᛶ⬟໬ࡀ㐍ࢇ࡛࠸ࡿࠋ☢ሙࡢᆒ୍໬ᢏ⾡ࡢ㐍ᒎ࡟ࡼࡾࠊ㧗ᗘ࡞⁐፹ᾘཤࡶྍ⬟࡜࡞ࡾࠊỈࢆྵࡴ⏕య⣔ヨᩱ࡬ࡢᛂ⏝ࡶྍ⬟࡟࡞ࡗࡓࡇ࡜࠿
ࡽࠊ࣓ࢱ࣑࣎ࣟࢡࢫ࡬ࡢᛂ⏝ࡢྍ⬟ᛶࡶ኱ࡁࡃ⭾ࡽࢇ࡛࠸ࡿࠋ

benchtop NMR㸪metabolomicsż࠶࠸ࡊࢃ࡜ࡶࡸࡍ㸪ࡑࢇࡎࡣ࠾㸪࠿ࢇࡾ㸪ࡋࡻ࠺࠿ࡁ㸪ࡇࡋࡆࢇ㸪࠾࠾࡟ࡋࡺ࠺ࡁ㸪࠾ࡉࡔࡏ࠸ࡌ㸪ࡃࡵࡓࡦࢁࡺࡁ㸪ࡃࡲࡁࡸࡍࡦࢁ㸪ࡸࡲ࠺ࡕ࠿ࡎ࠾

－ 126 －༟ୖNMR⿦⨨ࢆ⏝࠸࡚ࠊ㧗ᗘ࡟௦ㅰ⏘≀ࡢྠᐃ࣭ᐃ㔞ゎᯒࢆ⾜࠺ᢏ⾡ࢆ☜❧ࡍࡿࡓࡵ࡟ࡣࠊ
పឤᗘ࡛ศゎ⬟ࡀప࠸ࢫ࣌ࢡࢺࣝ࠿ࡽ࡝ࡢࡼ࠺࡟㧗ᗘ࡞᝟ሗࢆᘬࡁฟࡍ࠿࡜࠸࠺ㄢ㢟ࢆࢡࣜ࢔ࡍࡿᚲせࡀ࠶ࡿࠋᮏⓎ⾲࡛ࡣࠊ㉸ఏᑟ㧗☢ሙNMR࡟ࡼࡿẕஙࡸ౽➼ࡢ⏕యヨᩱࡢゎᯒ⤖ᯝ࡜ࡢẚ
㍑➼࡟ࡼࡾࠊ༟ୖNMRࡢ࣓ࢱ࣑࣎ࣟࢡࢫศ㔝࡬ࡢᛂ⏝ࡢྍ⬟ᛶ࡟ࡘ࠸࡚ࡢ᳨ウ࡟ࡘ࠸࡚ሗ࿌ࡍ
ࡿࠋ㸦㸯㸧 ࣄࢺẕங୰ࡢ࣓ࢱ࣎ࣛ࢖ࢺࡢゎᯒࣄࢺẕங୰ࡢ୺せ࡞పศᏊ௦ㅰ≀ࡢ1ࡘ࡟⢾ࡀ࠶ࡆࡽࢀࠊஙඣࡢ࢚ࢿࣝࢠ࣮※࡜ࡋ࡚㔜せ࡛࠶ࡿࣛࢡࢺ࣮ࢫࡢࡳ࡞ࡽࡎࠊከ✀㢮ࡢࣄࢺ࣑ࣝࢡ࢜ࣜࢦ⢾㸦HMO㸧ࡀྵࡲࢀࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࠋ
HMOࡣࠊࣛࢡࢺ࣮ࢫࠊ⬡㉁࡟ḟ࠸࡛ྵ㔞ࡢከ࠸ᅛᙧᡂศ࡛࠶ࡾࠊ⺮ⓑ㉁ࡼࡾࡶ㧗⃰ᗘ࡛ྵࡲࢀࡿࠋ
≉࡟ึங୰࡛ࡢྵ㔞ࡀከࡃࠊ௚ࡢᰤ㣴ᡂศ࡜ࡣ␗࡞ࡾࠊᑠ⭠࡛ࡢᾘ໬ࡸ྾཰ࢆཷࡅࡎ࡟኱⭠ࡲ࡛฿㐩ࡍࡿࡇ࡜࡛ࠊ᭷⏝⭠ෆ⣽⳦ࡢቑṪࡸᐃ╔ࡢಁ㐍࡞࡝ࡢ⭠ෆ⣽⳦ྀࡢᙧᡂࠊ᭷ᐖ⣽⳦ࡸ࢘࢖ࣝ
ࢫࡢ௜╔ࡢ㜵Ṇ࡟ᐤ୚ࡍࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿࠋࡲࡓࠊ୍㒊ࡢ྾཰ࡉࢀࡓHMOࡣࠊ⅖⑕ᛶࢧ࢖ࢺ࢝
࢖ࣥࡢⓎ⌧ࡢᢚไ➼ࢆ௓ࡋ࡚ࠊච␿ᶵ⬟ࡢㄪ⠇࡟ࡶ㛵୚ࡍࡿࡇ࡜࡞࡝ࡶሗ࿌ࡉࢀ࡚࠸ࡿࠋ
⌧ᅾࡲ࡛150✀㢮ࢆ㉸࠼ࡿHMOࡢ໬Ꮫᵓ㐀ࡀሗ࿌ࡉࢀ࡚࠸ࡿࡀࠊࡑࡢ୰࡛2'-ࣇࢥࢩࣝࣛࢡࢺ࣮
ࢫ㸦2'-FL㸧ࡣࠊẕங୰࡟᭱ࡶከࡃྵࡲࢀࡿHMOࡢ1ࡘ࡛࠶ࡾࠊ㏻ᖖࡑࡢ㔜㔞ࡢ25%⛬ᗘࢆ༨ࡵࡿࠋ
ࡋ࠿ࡋࠊ2'-FLࡢศἪ࡟ࡣࠊĮ-(1, 2)-ࣇࢥࢩࣝࢺࣛࣥࢫࣇ࢙࣮ࣛࢮࢆࢥ࣮ࢻࡍࡿFUT2㑇ఏᏊࡀ㛵୚ࡋ࡚࠾ࡾࠊࡇࡢ㓝⣲ࢆྜᡂ࡛ࡁࡿศἪᆺ࡜ࠊྜᡂ࡛ࡁ࡞࠸㠀ศἪᆺࡢẕぶࡀᏑᅾࡍࡿࠋ2'-FLࡢᕤᴗⓗ࡞኱㔞⏕⏘ࡀྍ⬟࡜࡞ࡗࡓࡇ࡜࡛ࠊᾏእ࡛ࡣᕷ㈍ࡢேᕤங࡬ࡢῧຍࡶ㛤ጞࡉࢀ࡚࠸ࡿࡇ࡜࠿
ࡽࠊศἪᆺ࣭㠀ศἪᆺࡢุูࡸẕங୰࡟ྵࡲࢀࡿࡑࡢ⃰ᗘࡢᐃ㔞ࡣ⮫ᗋⓗ࡟ࡶ㔜せ࡞ព࿡ࢆᣢࡘ
࡜⪃࠼ࡽࢀࡿࡀࠊᮍࡔ⡆౽࡞ᐃ㔞ἲࡣ☜❧ࡉࢀ࡚࠸࡞࠸ࠋ
ࡑࡇ࡛ᮏ◊✲࡛ࡣࠊ60 MHzࡢ༟ୖNMR⿦⨨ࢆ⏝࠸ࡓࠊẕங୰ࡢHMOࡢศᯒ࡟ࡘ࠸᳨࡚ウࡋࡓࠋ
2'-FLࡢࣇࢥ࣮ࢫࣘࢽࢵࢺࡢ࣓ࢳࣝᇶࡢࣆ࣮ࢡࢆゎᯒࡍࡿࡇ࡜࡟ࡼࡾࠊࡑࡢࢻࢼ࣮ࡢศἪᆺ࣭㠀ศἪᆺࢆ᫂☜࡟ุูࡍࡿࡇ࡜࡟ᡂຌࡋࡓࠋࡉࡽ࡟ࠊྠᵝ࡟ࣇࢥ࣮ࢫࣘࢽࢵࢺࢆ᭷ࡍࡿ୺せ࡞HMO࡛
࠶ࡿࠊ3-ࣇࢥࢩࣛࢡࢺ࣮ࢫ㸦3-FL㸧ࡸࣛࢡࢺ-N-ࣇࢥ࣌ࣥࢱ࣮࢜ࢫ-I㸦LNFP-I㸧ࢆゎᯒ࡟ຍ࠼ࡿࡇ࡜
࡛ࠊ㉸ఏᑟ㧗☢ሙNMR⿦⨨࡜Ⰻ࠸┦㛵ࡢ࠶ࡿᐃ㔞ⓗ࡞ゎᯒ⤖ᯝࢆᚓࡿࡇ࡜࡟ᡂຌࡋࡓࠋ
㸦㸰㸧 DSS⭠⅖ࣔࢹ࣐ࣝ࢘ࢫ౽୰ࡢ࣓ࢱ࣎ࣛ࢖ࢺࡢゎᯒᚑ᮶ࠊ⏕యヨᩱࡢ࣓ࢱ࣑࣎ࣟࢡࢫࡢᑐ㇟࡜ࡋ࡚ࡣࠊ⾑ᾮࡸᒀ࡞࡝ࡢయᾮࡀከࡃ⏝࠸ࡽࢀ࡚ࡁࡓࠋ
ࡋ࠿ࡋ࡞ࡀࡽࠊ㏆ᖺࠊ⭠ෆ⣽⳦ྀࡢᐟ୺ࡢᜏᖖᛶࡢ⥔ᣢ࡬ࡢ㔜せᛶࡀ᫂ࡽ࠿࡟࡞ࡗ࡚ࡁࡓࡇ࡜࠿
ࡽࠊ౽ヨᩱࢆᑐ㇟࡜ࡋࡓゎᯒ౛ࡶቑຍࡋ࡚࠸ࡿࠋ౽ヨᩱࢆᑐ㇟࡜ࡋࡓ࣓ࢱ࣑࣎ࣟࢡࢫ࡛ࡣࠊࡑࡢ
ヨᩱㄪ〇ࡸ๓ฎ⌮ࡢ⡆౽ࡉ➼࠿ࡽࠊNMR࡟ࡼࡿゎᯒࡣ≉࡟ඃ఩࡞Ⅼࡀከ࠸࡜⪃࠼ࡽࢀࡿࠋ
ᮏ◊✲࡛ࡣࠊ₽⒆ᛶ኱⭠⅖࡜㢮ఝࡢ⑕≧ࢆᘬࡁ㉳ࡇࡍࠊࢹ࢟ࢫࢺࣛࣥ◲㓟ࢼࢺ࣒ࣜ࢘㸦DSS㸧ㄏᑟᛶ⭠⅖ࣔࢹࣝࡢ࣐࢘ࢫ⏤᮶ࡢ౽ヨᩱࢆ⏝࠸࡚ࠊ༟ୖNMR⿦⨨࡟ࡼࡿ⑌ᝈࡢุูศᯒࡸ࣓ࢱ࣎ࣛ
࢖ࢺࡢᐃ㔞࡟㛵ࡍࡿᇶ♏ⓗ࡞᳨ウࢆ⾜ࡗࡓࠋDSS⭠⅖ࣔࢹࣝ⩌࡜ࢥࣥࢺ࣮ࣟࣝ⩌ࡢ౽࠿ࡽࠊ⦆⾪ᾮῧຍ࡜ᨩᢾࠊ㐲ᚰࡢࡳࡢࡈࡃ⡆౽࡞᪉ἲ࡛ᢳฟࡋࡓỈ⁐⏬ศࢆᑐ㇟࡜ࡋ࡚ࠊ800 MHzࡢ㉸ఏᑟ㧗☢ሙཬࡧ60 MHzࡢ༟ୖNMR⿦⨨ࢆ⏝࠸ࡓᐃࢆ⾜࠸ࠊࣀࣥࢱ࣮ࢤࢵࢺ࡛ࡢከኚ㔞ゎᯒࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊ࠸ࡎࢀࡢ⿦⨨ࡢࢫ࣌ࢡࢺࣝࢆ⏝࠸࡚ࡶࠊయ㔜ῶᑡ➼ࡢ㔜⠜࡞⑕≧ࡀࡳࡽࢀࡿ๓࡟ࠊ
DSS⭠⅖ࣔࢹࣝ⩌࡜ࢥࣥࢺ࣮ࣟࣝ⩌ࡢุูࡀྍ⬟࡛࠶ࡿࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗࡓࠋࡲࡓࠊ୧⩌ࢆ༊ูࡍࡿ㔜せ࡞௦ㅰ⏘≀࡜ࡋ࡚ྠᐃࡉࢀࡓ㓑㓟ࢆᑐ㇟࡟ࡋ࡚ࠊ༟ୖNMRࢫ࣌ࢡࢺࣝ࠿ࡽࡢᐃ㔞ἲ࡟ࡘ࠸᳨࡚ウࡋࠊಙ㢗ᛶࡢ㧗࠸⤖ᯝࢆᚓࡿࡇ࡜࡟ࡶᡂຌࡋࡓࠋ

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ࣇ ࣝ ࢜ ࣟ ࢟ ࣀ ࣟ ࣥ ໬ ྜ ≀ ࡜RNA࡜ ࡢ ┦ ஫ స ⏝ ゎ ᯒ 㸸 ㏆ ᥋ ࡍࡿሷᇶᑐࡢᙳ㡪ࡢゎᯒ‫୍ۑ‬ᲄ᲍ⰼ㸪ୖᮧᏕ㸪Ἑྜ๛ኴ
༓ⴥᕤᴗ኱Ꮫ㸪ᰴᘧ఍♫Veritas In SilicoInteraction between fluoroquinolone derivatives and RNA: effect of base pairs
adjacent to the bulge out residuesżRika Ichijo1, Takashi Kamimura2, Gota Kawai11

Chiba Institute of Technology, 2Veritas In Silico Inc.
Interaction analysis between small molecules and RNA are important for the RNA-targeted

drug discovery. We have demonstrated, by NMR, that a fluoroquinolone derivative, KG022,
interacts with the RNAs in the vicinity of the bulge residue, with preferring C and G as thebulge residues 1) . In order to further characterize the interaction between KG022 and RNA,base pairs adjacent to the bulge-out residue were mutated. In the present study, RNAs withvariations in the 3ƍ side of the bulge-out G residue were analyzed to find that AU and GC basepairs are preferred to UA and CG base pairs.
ᗎㄽᮏ◊✲࡛ࡣ㸪RNA ࢆࢱ࣮ࢤࢵ

A㻌
C㻌
B㻌
ࢺ࡜ࡋࡓపศᏊ๰⸆ࢆࡵࡊࡋ㸪ࣇࣝ࢜ࣟ࢟ࣀࣟࣥㄏᑟయ࡛࠶ࡿ
KG022㸦Fig. 1A㸧࡟╔┠ࡋࡓゎᯒࢆ㐍ࡵ࡚࠸ࡿ㸬KG022 ࡜ RNA ࡜ࡢ┦஫స⏝ࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵ㸪NMR ἲ࡟ࡼࡿ┦஫స⏝ゎᯒࢆ⾜ࡗ࡚࠸ࡿ㸬ࡇࢀࡲ࡛ࡢゎᯒ
Fig. 1. KG022 and Design of model RNAs 㻌࡟ࡼࡾ㸪KG022 ࡣ C ࣂࣝࢪ࠶ࡿ
A: a fluoroquinolone derivative, KG022, B: RNA-G, C:
RNA-G-3AU-uucg. The base-pair at the 3ƍ side of the࠸ࡣ G ࣂࣝࢪࢆᣢࡘ RNA ࡜┦
bulge-out residue was mutated. 㻌஫స⏝ࡍࡿࡇ࡜ࡀ♧ࡉࢀ࡚࠸ࡿ
1)㸬ࡇࢀࡲ࡛ࡢ◊✲࡛ࡣ Fig. 1B ࡟♧ࡍ RNA ࢆ⏝࠸࡚࠸ࡓࡓࡵ㸪5 ሷᇶ࠿ࡽ࡞ࡿ࣮ࣝࣉࡢᦂࡽ
ࡂࡀ኱ࡁࡃࡑࡢ㒊ศࡢᵓ㐀ࡀ཰᮰ࡋ࡞࠿ࡗࡓࡓࡵ㸪ᮏ◊✲࡛ࡣᏳᐃ࡞ UUCG ࣮ࣝࣉ࡟ኚ᭦ࡋ
ࡓ RNA ࢆ⏝࠸ࡓ㸦Fig. 1C㸧㸬RNA-C-3AU-uucg ࡜ RNA-G-3AU-uucg ࡢࡑࢀࡒࢀࡢ」ྜయࡢ❧యᵓ㐀ィ⟬ࢆ⾜ࡗࡓ⤖ᯝ㸪௨๓࡜ྠᵝ࡟ KG022 ࡢࢩࢡࣟࣉࣟࣃࣥ⎔࡜㞄᥋ࡍࡿࡼ࠺࡞ᵓ㐀ࢆ࡜ࡗ࡚࠸ࡓ㸬ࡑࡇ࡛㸪ࣂࣝࢪ࢔࢘ࢺṧᇶࡢ㏆ഐࡢሷᇶᑐࢆኚ᭦ࡋࡓ RNA ࢆ C ࣂࣝࢪ࡜ G ࣂࣝࢪ࡛ࡑࢀࡒࢀタィࡋ㸪NMR ࢫ࣌ࢡࢺࣝࡢゎᯒ࠾ࡼࡧ❧యᵓ㐀ィ⟬ࢆ㐍ࡵ࡚࠸ࡿ㸬௒ᅇࡣ㸪ࣂࣝࢪ࢔࢘ࢺṧᇶࡢ3ƍഃࡢሷᇶᑐࢆኚ᭦ࡋࡓGࣂࣝࢪࡢRNAࢆGࢩ࣮ࣜࢬ࡜ࡋ㸪
ྛRNAࡢNMRゎᯒࢆ⾜࠸㸪ࡉࡽ࡟ྛRNA࡟KG022ࢆῧຍࡋࡓ㝿ࡢࢫ࣌ࢡࢺࣝࢆẚ㍑ࡋࡓ㸬ࣇࣝ࢜ࣟ࢟ࣀࣟࣥ㸪RNAࢱ࣮ࢤࢵࢺ๰⸆
‫࠿ࡾ࠺ࡻࡌࡕ࠸ۑ‬㸪࠿ࡳࡴࡽࡓ࠿ࡋ㸪࠿ࢃ࠸ࡈ࠺ࡓ

－ 134 －

RNA-G-3AU-uucg㻌

RNA-G-3GC-uucg㻌

RNA-G-3CG-uucg㻌

RNA-G-3UA-uucg㻌

Fig. 2. Imino proton spectra of the model RNAs㻌RNA-G-3AU-uucg

RNA-G-3GC-uucg㻌

RNA-G-3UA-uucg㻌

RNA-G-3CG-uucg㻌

Fig. 3. HOHAHA spectra of the model RNAs᪉ἲRNA ヨᩱࡣ໭ᾏ㐨ࢩࢫࢸ࣒ࢧ࢖࢚ࣥࢫᰴᘧ఍♫࡟ጤクྜᡂࡋࡓ㸬⁐፹࡜ࡋ࡚ 5%㔜Ỉ㸦99.98
atom㸣㸪኱㝧᪥㓟♫㸧࠾ࡼࡧ 50 mM ሷ໬ࢼࢺ࣒ࣜ࢘ྵࡴ 20 mM ࣜࣥ㓟ࢼࢺ࣒ࣜ࢘⦆⾪ᾮ㸦pH 6.5㸧ࢆ⏝࠸ࡓ㸬AvanceNeo600 ศගィ㸦Bruker ♫㸧ࢆ⏝࠸࡚ 288 K ࡛

ᐃࢆ⾜ࡗࡓ㸬⤖ᯝࡑ ࢀ ࡒ ࢀ ࡢ RNA࡟ KG022ࢆ ῧ ຍ ࡋ ࡓ 㝿 ࡢ ࢖ ࣑ ࣀ ࣉ ࣟ ࢺ ࣥ ࢫ ࣌ ࢡ ࢺ ࣝ ࢆ ẚ ㍑ ࡍ ࡿ ࡜ 㸪ࣂ ࣝ ࢪ ࢔ ࢘ ࢺ ṧ ᇶ ࡢ 3ƍഃ ࡀ AUሷ ᇶ ᑐ ࡛ ࠶ ࡿ RNA-G-3AU-uucg࠾ ࡼ ࡧ ࡑ ࢀ ࢆ GCሷ ᇶ ᑐ ࡟ኚ ࠼ ࡓ RNA-G-3GC-uucg࡛ ࡣ 」 ྜ య ࡢ ࢩ ࢢ ࢼ ࣝ ࡀ ᫂ ☜ ࡟ ほࡉ ࢀ ࡓ ࡀ 㸪 RNA-G-3CG-

uucg࠾ ࡼ ࡧ RNA-G-3UA-uucg࡛ ࡣ ࢩ ࢢ ࢼ ࣝ ࡀ ࡸ ࡸ ࣈ ࣟ ࣮ ࢻ ࡛ ࠶ ࡾ 㸪 ሷ ᇶ ᑐ ≉ ␗ ᛶ ࡀ ࠶ ࡿࡇ ࡜ ࡀ ☜ ㄆ ࡉ ࢀ ࡓ 㸦 Fig. 2㸧 㸬ῧ ຍ ๓ ࡜ ῧ ຍ ᚋ ࡢ HOHAHAࢫ ࣌ ࢡ ࢺ ࣝ ࢆ ẚ ㍑ ࡍ ࡿ ࡜ 㸪 ࠸ ࡎ ࢀ ࡢ RNA࡛ ࡶ ୍ 㒊 ࡢ ࢩ ࢢࢼ ࣝ ࡀ ኚ ໬ ࡋ ࡚ ࠸ ࡓ 㸦 Fig. 3㸧 㸬 RNA-G-3CG-uucg࡛ ࡣ KG022ࡢ ῧ ຍ ࡟ ࡼ ࡾ ࢩ ࢢ ࢼ ࣝ ࡀቑ ࠼ ࡚ ࠾ ࡾ 㸪 ୍ ᪉ 㸪 RNA-G-3UA-uucg࡛ ࡣ ࠸ ࡃ ࡘ ࠿ ࡢ ࢩ ࢢ ࢼ ࣝ ࡀ ᾘ ኻ ࡋ ࡓ 㸬⪃ᐹ࢖ ࣑ ࣀ ࣉ ࣟ ࢺ ࣥ ࢫ ࣌ ࢡ ࢺ ࣝ ࡜ HOHAHAࢫ ࣌ ࢡ ࢺ ࣝ ࡢ ゎ ᯒ ࠿ ࡽ 㸪 KG022ࡀ ࣂ ࣝ ࢪ ࢔ ࢘ࢺṧᇶ࡜ᮎ➃࡟⤖ྜࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬ࡇࡢ࠺ࡕࣂࣝࢪ࢔࢘ࢺṧᇶ࡜ࡢ┦஫స ⏝ ࡣ 㸪 3ƍഃ ࡢ ሷ ᇶ ᑐ ࡟ ࡼ ࡗ ࡚ ᙳ 㡪 ࢆ ཷ ࡅ ࡚ ࠸ ࡿ ྍ ⬟ ᛶ ࡀ ࠶ ࡿ 㸬௒ ᚋ ࡣ 㸪 RNA-G-3AU-uucg࡜ RNA-G-3GC-uucg࡟ ࡘ ࠸ ࡚ ࡢ 」 ྜ య ࡢ ❧ య ᵓ 㐀 ࢆ Ỵ ᐃࡋ 㸪 ࡇ ࢀ ࡜ RNA-Gࡢ 」 ྜ య ࡢ ᵓ 㐀 ࡜ ẚ ㍑ ࡍ ࡿ ࡇ ࡜ ࡟ ࡼ ࡗ ࡚ 㸪 Gࢩ ࣜ ࣮ ࢬ ࡢ ྛ RNA࡜KG022ࡢ ⤖ ྜ ᵝ ᘧ ࢆ ᫂ ࡽ ࠿ ࡟ ࡋ ࡓ ࠸ 㸬 ࡲ ࡓ 㸪 Cࢩ ࣜ ࣮ ࢬ ࡟ ࡘ ࠸ ࡚ ࡶ ゎ ᯒ ࢆ 㐍 ࡵ ࡚ ࠸ ࡿ 㸬ཧ⪃ᩥ⊩
1. Nagano, K., Kamimura, T. and Kawai, G., J. Biochem. 171, 239-244 (2022).

－ 135 －

P3

Ỉ⁐ᾮヨᩱ࡟࠾ࡅࡿ 3XUH6KLIWᐃࡢヨࡳ‫ۑ‬㧗ᶫᚁ୕ࠊἙྜ๛ኴ
༓ⴥᕤ኱࣭኱Ꮫ㝔⏕࿨⛉Ꮫ◊✲⛉

Pure shift NMR of absorption-mode lineshapes has become one of the standard
techniques for suppressing multiplets. Although a number of techniques have been
proposed, the Zangger and Sterk (ZS) and PSYCHE methods seem to be the best choicefor now. However, these techniques are not applicable to the aqueous solutions wherea strong solvent signal co-exists with weak signals of interest. We found additionalsignal refocusing is quite effective for suppressing the solvent signal in addition to thepre-saturation
1H-NMR࡟࠾࠸࡚ Shift ᝟ሗ࡜ J-⤖ྜࢆศ㞳ࡍࡿヨࡳࡣ᫇࠿ࡽࡢㄢ㢟࡛ࠊ࠸ࢃࡺࡿ

J-resolve 2 ḟඖ NMR ἲࡢฟ⌧௨᮶ࠊከࡃࡢヨࡳࡀ⾜ࢃࢀ࡚ࡓࠋ࡜ࡃ࡟ J-resolve 2 ḟඖἲࡀࣃ࣮࣡ࢫ࣌ࢡࢺࣝࡋ࠿ᚓࡽࢀ࡞࠸ࡇ࡜࠿ࡽࠊಙྕࡢ㔜࡞ࡾࢆṇࡋࡃホ౯࡛ࡁࡿ྾཰࣮ࣔ
ࢻ࡛ࢫ࣌ࢡࢺࣝࢆᚓࡿᡭẁࡀồࡵࡽࢀࡓࠋࡋ࠿ࡋᥦ᱌ࡉࢀࡓ᪉ἲࡣఱࢀࡶឤᗘࡢపୗ࡜࠸
࠺⮴࿨ⓗ࡞ḞⅬࢆᢪ࠼ࠊ࠸ࡎࢀࡶᐇ⏝໬࡟ࡣᅔ㞴ࢆ࡜ࡶ࡞ࡗࡓࠋ1997 ᖺ࡟ Zagger ࡜ Sterk
ࡣ㑅ᢥࣃࣝࢫ࡜☢ሙ໙㓄ࢆ⤌ࡳྜࢃࡏࡿ᪉ἲ࡛ึࡵ࡚ᐇ⏝ⓗ࡞᪉ἲࢆᥦ᱌ࡋࡓࠋᙼࡽࡢ࢔
࢖ࢹ࢔ࢆࡶ࡜࡟ Manchester ࢢ࣮ࣝࣉࡣ PSYCHE ἲࢆᥦ᱌ࡋࠊ⌧ᅾࡣ⏝㏵࡟ᛂࡌ࡚ࡇࢀࡽ
㸰ࡘࡢ᪉ἲࡀ౑ࢃࢀ࡚࠸ࡿࠋ ࡋ࠿ࡋࡇࢀࡽࡢ᪉ἲࡣࠊཎ⌮ⓗ࡟ࢫࣆ࢚ࣥࢥ࣮㛫㝸ࢆኚ࠼࡚ FID ࢆࣈࣟࢵࢡ༢఩࡛ྲྀࡾ㎸ࡴ᪉ἲ࡛࠶ࡾࠊ
ᐇ㝿ࡣಙྕࡢῶ⾶ࡀᏳᐃࡋ࡞࠸ࡓࡵ
ᅗ 1 ࡟♧ࡍࡼ࠺࡟ࠊFID ಙྕࡣ୙㐃⥆࡟᥋⥆ࡉࢀ࡚ࡋࡲ࠺ࠋ㹖ࢳࣕࣥࢿࣝࢆ㐃⥆࡟࡞ࡿࡼ࠺ࣃ࣓࣮ࣛࢱࢆㄪ
ᩚࡍࡿࡇ࡜ࡣ࡛ࡁ࡚ࡶࠊ㹗ࢳࣕࣥࢿࣝࡢಙྕ࡜ྠ᫬࡟ㄪᩚࡍࡿࡇ࡜ࡣ୙

Fig.1 Typical FID of an aqueous sample recon-ྍ⬟࡛࠶ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋࢯࣇࢺ

structed by PSYCHE method.

࡛㐃⥆࡟ࡘ࡞࠸࡛ࡶ⤖ᯝࡣⰾࡋࡃ࡞

show X and Y channel signals, respectively.

Left and right࠿ࡗࡓࠋ㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝㹝
Pure shift NMR, Ỉ⁐ᾮ ࣃࣝࢫิ‫ࡓ࠺ࡈ࠸ࢃ࠿ࠊ࠺ࡒ࠸ࡏࡋࡣ࠿ࡓۑ‬－ 136 －

ࡑࡇ࡛ Presaturation ࢆヨࡳࡓࡀࠊ
Delay ࡀ኱ࡁࡃ࡞ࡿ࡜ಙྕࡀᅇ᚟ࡋ
ṇᖖ࡞ FID ࡢ෌ᵓᡂࡀᅔ㞴࡛࠶ࡿ

180ι

180ι

‫ݐ‬ଵ Ȁʹ૚۶‫ݐ‬ଵ Ȁʹࡇ࡜ࡀศ࠿ࡗࡓࠋ࠸ࡃࡘ࠿ࡢヨ⾜ࡢᚋࠊPSYCHE ࣃࣝࢫ࡟ refocus ࣃ㻳㼦ࣝࢫ࡜ chirp ࣃࣝࢫࢆຍ࠼ࡿ᪉ἲࡀ
᭱ࡶຠᯝⓗ࡛࠶ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ
(ᅗ 2)ࡇࡢ᪉ἲ࡛ H2O ಙྕᢚไࡀ୙༑
ศ࡞ሙྜࡣࠊ50uW ⛬ᗘࡢ presaturation ࢆࡍࡿ࡜༑ศ࡞ᯝࡀᚓࡽࢀࡓࠋ
ᅗ 3 ࡟ 1.3mg/0.5mL ࡛

Fig.2.

Modified PSYCHE pulse sequencefor H2O solutions.
pulse are added.

Refocus and Chirp

It is preferable to add

another pre-saturaton pulse for further
suppression of H2O signal.

ᐃࡋࡓL-ࣇ࢙ࢽࣝ࢔ࣛࢽࣥࡢ⤖ᯝࢆ♧ࡍࠋ୍␒ୖࡢࢫ࣌ࢡࢺࣝࡣ✚⟬࡞ࡋ࡛ᐃࡋࡓཧ↷ࢹ࣮ࢱࢆ♧ࡍࠋ┿ࢇ୰ࡢࢫ࣌ࢡࢺࣝࡣྠ୍⃰ᗘࡢ㔜Ỉ⁐ᾮ࡟࠾ࡅࡿ Modified PSYCHE ࢫ࣌ࢡࢺ࡛ࣝ࠶ࡿࠋ᏶඲࡟⁐፹ಙྕࡀᢚไ
ࡉࢀ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡿࠋୗࡢᅗࡣ

‫ܦ‬ଶ ܱ
‫ܦ‬ଶ ܱ

㻤䇻㻠㻠䇿‫ܪ‬ଶ ܱ

㻟㻠䇻㻟㻢䇿

㍍Ỉ⁐ᾮࡢ⤖ᯝ࡛࠶ࡿࠋࡇࡢሙྜ
1uW ࡢ pre-saturation ࢆ࠿ࡅࡓࠋ
Ỉಙྕࡀⱝᖸṧࡗ࡚࠸ࡿࡓࡵࠊឤᗘ

Fig.3. Spectra of L-Phe(1.3mg/0.5mL) areࡣ㔜Ỉ୰ࡢ⣙༙ศ࡟పୗࡋ࡚࠸ࡿࠋ

shown in D2O and H2O. The result shows

refocus ࣃࣝࢫิࢆ⧞ࡾ㏉ࡋ࡚ࡶ

a substantial decrease in sensitivity com-㢧ⴭ࡞ࢫ࣌ࢡࢺࣝࡢᨵၿࡣぢࡽࢀ࡞

pairing to the normal spectrum, and H2O.

࠿ࡗࡓࠋ⤖ㄽ࡜ࡋ࡚ࠊಙྕࡢᙉᗘẚsolution loses another factor of 2 than D2Oࡀ኱ࡁࡃ␗࡞ࡿ᫬ࡣࠊFID ࡀ㐃⥆࡟solution.

⧅ࡀࡽ࡞࠸ࡓࡵࠊぢ࠿ࡅୖࡢ S/N ẚࡀపୗࡍࡿࠋᚑࡗ࡚ఱࡽ࠿ࡢ᪉ἲ࡛ᙉᗘࢆᢚ࠼ࡿᚲせࡀ࠶ࡾࠊrefocus ࣃࣝࢫ࡜ chirp ࣃࣝࢫࡢ⤌ࡳྜࢃࡏࡣ୍ࡘࡢ᭷ຠ࡞᪉ἲ࡛࠶ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ

－ 137 －

P4Y

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G=  }®  '14ÃÓÝ(8Q:SHÌÃÓ ¡¹Â 6*&! 6&－ 138 －

'"4$Öc)¥( @T<Ð(7j7ÕO 

?6

EJ

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(7j7ÕO Uy   «¸7«¸')  ,+(50"0.#(1+.+"0%5("*"

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2'  :8#K!(L$`!(L7
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513

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¿25 
B xw(C&4]57ÕO  &$  %")0&  +# 0%" ,.+" %"! *! &0/,".&,%".( #+.  "-1&,)"*0 #+. 

      


*! *! &)$&*$

－ 139 －

P5

∦ ഃ 㛤 ᨺ ᆺ 105࡟ ࡼ ࡿ ᘓ ⠏ ᮦ ᩱ ࡢ ྵ Ỉ ⋡ ࡢ ཎ ఩ ⨨ ࣭ 㠀 ◚ ቯ ィ࡟ࡴࡅ࡚‫ۑ‬୰ᓥ ၿே⏘ᴗᢏ⾡⥲ྜ◊✲ᡤ ᆅᅪ㈨※⎔ቃ◊✲㒊㛛

Nondestructive in-site moisture quantification of building materials bysingle-sided NMRżYoshito Nakashima 1
1

National Institute of Advanced Industrial Science and Technology
A portable single-sided NMR surface scanner was applied to the nondestructive

quantification of the moisture in slaked lime plaster samples. The lightweight sensor unit (§4kg) developed is potentially capable of probing a portion §1 cm beneath the plaster wall of thearchitectural heritage. Measurements of a drying plaster plate sample were successfully
performed in a laboratory to monitor the CPMG signal decrease with decreasing sample weight.
Thus, the single-sided NMR system is a promising in-situ nondestructive tool for the
maintenance and remediation of the cultural heritage made of plaster.
ࡣࡌࡵ࡟⪁ ᮙ ໬ ࡋ ࡓ ࠊ࠶ ࡿ ࠸ ࡣ ᪋ ᕤ ┤ ᚋ ࡢ ᘓ 㐀 ≀ ࡛ ࡣ ࠊᘓ 㐀 ≀ ⾲ 㠃 ࡟ ࠶ ࡿ ᘓ ⠏࣭ᆅ ┙ ᮦ ᩱ ࡢ య✚ ྵ Ỉ ⋡ ࢆ ཎ ఩ ⨨ ࡛ 㠀 ◚ ቯ ࢭ ࣥ ࢩ ࣥ ࢢ ࡋ ࡓ ࠸ ࢽ ࣮ ࢬ ࡀ ࠶ ࡿ ࠋࡇ ࡢ ࢽ ࣮ ࢬ ࡟ ྜ ࢃ ࡏ ࡿ ࡓ ࡵ࡟ ࠊ ࣉ ࣟ ࢺ ࣥ ᰾ ☢ Ẽ ඹ 㬆 ࢆ ཎ ⌮ ࡜ ࡍ ࡿ ∦ ഃ 㛤 ᨺ ᆺ ࡢ 105≀ ⌮ ᥈ ᰝ ⿦ ⨨ ࢆ 㛤 Ⓨ ࡋ ࡚ ࠸ ࡿ ࠋࡑ ࡢ ᇶ ᮏ ᛶ ⬟ ࢆ ⤂ ௓ ࡍ ࡿ ࡜ ࡜ ࡶ ࡟ ࠊ࡜ ࡃ ࡟ ᇛ 㒌 ࡞ ࡝ ࡢ ୡ ⏺ 㑇 ⏘࣭ᅜ ᐆ ⣭ ᘓ ⠏ ≀ ࡛ ከ ⏝ ࡉࢀ࡚࠸ࡿ⁽႞ࡢ⌧ሙ࡛ࡢỈศィࢆ ព ㆑ ࡋ ࡓ ᐊ ෆ ᐇ 㦂 ࢆ ሗ ࿌ ࡋ ࡓ ࠸ >@ࠋ ᐇ㦂∦ഃ㛤ᨺᆺࡢィࢩ ࢫ ࢸ ࣒ ࢆ )LJ࡟ ♧ ࡍ 㸦 ᒇ እ ࣀ ࢖ ࢬ ࣞ ࣋ ࣝ ࡢ ィࢆවࡡࡓヨ㐠㌿㢼 ᬒ 㸧ࠋࢿ ࢜ ࢪ ࣒ ☢ ▼ ࡜ 㧗 ࿘ Ἴ ࢥ ࢖ ࣝ ࠿ ࡽ ࡞ ࡿ ࢭ ࣥ ࢧ ࣮ ࣘ ࢽ ࢵ ࢺ ࡢ 㔜 㔞 ࡣ ⣙ NJ࡛ ࠶ ࡿ ࠋᖹ 㠃 ᆺ ࡢ 㧗 ࿘ Ἴ ࢥ ࢖ ࣝ ࠿ ࡽ FP⛬ ᗘ 㞳 ࢀ ࡓ ✵㛫 ࡟ 㟼 ☢ ሙ ࡀ ⣙ P7ࡢ ᆒ ୍ ࡞ 㡿 ᇦ ࡀ ⏕ ᡂ ࡉࢀ ࡿ ࡼ ࠺ ࡟ タ ィ ࡉ ࢀ ࡚ ࠾ ࡾ ࠊࡑ ࡇ ࡀ ឤ ᗘ 㡿 ᇦ࡟ ࡞ ࡿ ࠋࡇ ࡢ ࢭ ࣥ ࢧ ࣮ ࣘ ࢽ ࢵ ࢺ ࡢ ☢ Ẽ ᅇ ㊰ ࡣ105ಙ ྕ ᙉ ᗘ ࢆ ᨭ 㓄 ࡍ ࡿ 㔜 せ ࡞ 㛤 Ⓨ せ ⣲ ࡛ ࠶ࡾ ࠊ ⣙ ୓ ᅇ ࡢ 㟼 ☢ ሙ ࢩ ࣑ ࣗ ࣞ ࣮ ࢩ ࣙ ࣥ ࢆ࡬࡚ᑍἲࡸ☢ሙᙉᗘࢆ᭱㐺タィࡋࡓ࠺࠼࡛
᪂ つ ࡟ 〇 స ࡋ ࡓ ࠋࡑ ࡢ ⤖ ᯝ ࠊ௨ ๓ ࡢ ࢭ ࣥ ࢧ ࣮ࣘ ࢽ ࢵ ࢺ >@࡟ ẚ ࡭ ࡚ ឤ ᗘ 㡿 ᇦ ࡢ య ✚ ࢆ ⣙ )LJ3HUIRUPDQFHWHVWRIWKHVFDQQHUV\VWHPLQWKHRSHQDLU$ZDWHUVDWXUDWHG
SRURXVSODVWHUVDPSOHLVEHLQJPHDVXUHG∦ഃ㛤ᨺᆺ105ప☢ሙ᫬㛫㡿ᇦࣉࣟࢺࣥ105ཎ఩⨨࣭㠀◚ቯ᳨ᰝ‫࡜ࡋࡼࡲࡋ࠿࡞ۑ‬－ 140 －ቑ ࡸ ࡍ ࡇ ࡜ ࡟ ᡂ ຌ ࡋ ࡓ ࠋ ࡉ ࡚ ࠊ⁽ ႞ ࡣ ᾘ ▼ ⅊ ࡀ ୺ ᡂ ศ ࡛ ࠶ ࡿ ࡀ ࠊᾘ ▼ ⅊ ࡀ ኱ Ẽ ୰ ࡢ ஧ 㓟 ໬ Ⅳ ⣲ ࡜ ཯ ᛂ ࡍ ࡿ ࡇ ࡜࡛ ᙉ ᗘ ࡀ Ⓨ ⌧ ࡍ ࡿ ࡢ ࡛ ࠊỈ ࡜ ΰ ⦎ ࡋ ࡚ ቨ ࡟ ሬ ࡗ ࡓ ᚋ ࡟ ᚤ ᑡ ✵ 㝽 ࡀ ᪩ ࡃ ஝ ࡃ ࡇ ࡜ ࡀ 㔜 せ ࡛࠶ ࡿ ࠋ ࡋ ࡓ ࡀ ࡗ ࡚ ࠊ ሬ ࡾ ࡓ ࡚ ࡢ ZHW࡞ ≧ ែ ࡢ ⁽ ႞ ቨ ࡢ ෆ 㒊 ࡢ ஝ ⇱ ≧ ែ ࢆ ⌧ ሙ ࡛ 㠀 ◚ ቯ ࡛ࣔࢽࢱࣜࣥࢢィࡍ ࡿ ࡇ ࡜ ࡣ ࠊᇛ ቨ ࡞ ࡝ ࡢ ಟ ⧋ ࡢ ᪋ ᕤ ⟶ ⌮ ࡜ ࡋ ࡚ 㔜 せ ࡛ ࠶ ࡿ ࠋࡇ ࡢ ࡇ ࡜ࢆ ព ㆑ ࡋ ࡓ ୖ ࡛ ࠊከ Ꮝ ㉁ ⁽ ႞ ࣉ ࣞ ࣮ ࢺ ࡢ ஝ ⇱ 㐣 ⛬ ࡢ ࣔ ࢽ ࢱ ࣜ ࣥ ࢢ ࢆ ᐊ ෆ ࡛ ᐇ ᪋ ࡋ ࡓ ࠋ᭱ึ ࡣ ᏶ ඲ ࡟ Ỉ ࡛ 㣬 ࿴ ࡋ ࡚ ࠸ ࡓ ⁽ ႞ ࣉ ࣞ ࣮ ࢺ ࡢ ࢧ ࣥ ࣉ ࣝ㸦 య ✚ ྵ Ỉ ⋡ ⣙ YRO㸧ࢆ ஝ ⇱ ᶵ࡛ Υ ࡛ ஝ ⇱ ࡉ ࡏ ࡘ ࡘ ࠊᐃ ᮇ ⓗ ࡟ )LJDࡢ ࢥ ࢖ ࣝ ࡢ ୖ ࡟ ⨨ ࠸ ࡚ &30*ࣃ ࣝ ࢫ ࢩ ࣮ ࢣ ࣥ ࢫ ࡛ࣉ ࣟ ࢺ ࣥ ᶓ ⦆ ࿴ Ἴ ᙧ ࢆ ඹ 㬆 ࿘ Ἴ ᩘ 0+]࡛ ィࡋ ࡓ ࠋ ࢚ ࢥ ࣮ 㛫 㝸 ࡣ PVࠊ 5)ࣃ ࣝ ࢫ ᖜࡣ PVࠊ ಙ ྕ ✚ ⟬ ᅇ ᩘ ࡣ ᅇ ࠊ ࢩ ࣮ ࢣ ࣥ ࢫ ࡢ ⧞ ࡾ ㏉ ࡋ 㛫 㝸 ࡣ PV࡛ ࠶ ࡗ ࡓ ࠋ ⤖ᯝ࡜⪃ᐹ
&30*Ἴ ᙧ ࡢ ⤒ ᫬ ኚ ໬ ࢆ )LJE࡟ ࡋ ࡵ ࡍ ࠋ ᮇ ᚅ ㏻ ࡾ ࠊ ஝ ⇱ ࡀ 㐍 ⾜ ࡋ ࡚ ࠸ ࡃ ࡜ ࢮ ࣟ ᫬ ้࡟ እ ᤄ ࡋ ࡓ &30*Ἴ ᙧ ࡢ ಙ ྕ ᙉ ᗘ ࡀ ప ୗ ࡋ ࡚ ࠸ ࡃ㸦 ✵ 㝽 Ỉ ࡀ ⵨ Ⓨ ࡋ ࡚ ㏨ ࡆ ࡚ ࠸ ࡃ 㸧ᵝ Ꮚ ࡀ☜ ㄆ ࡛ ࡁ ࡓ ࠋᅗ ࡣ ┬ ␎ ࡍ ࡿ ࡀ ࠊ஝ ⇱ ࡟ ࡼ ࡿ ࢧ ࣥ ࣉ ࣝ ࡢ 㔜 㔞 ῶ ࡜ &30*ಙ ྕ ᙉ ᗘ ࡢ ప ୗ ࡣ 㧗࠸ ┦ 㛵 ࢆ ࡋ ࡵ ࡋ ࡓ ࠋ ࡞ ࠾ ࠊ )LJE࡛ ࡣ ஝ ⇱ ࡟ క ࠸ 7್ ࡢ ప ୗ ࡶ ☜ ㄆ ࡛ ࡁ ࡿ ࡀ ࠊ ࡑ ࡢ ⌮⏤ ࡣ ࠊ⁽ ႞ ୰ ࡢ ࡉ ࡲ ࡊ ࡲ ࡞ ࢧ ࢖ ࢬ ࡢ ᚤ ᑡ ✵ 㝽 ࡢ ࠺ ࡕ ẚ ㍑ ⓗ ኱ ࡁ ࡞ ࢧ ࢖ ࢬ ࡢ ✵ 㝽㸦 7ࡀ 㛗ࡵ 㸧 ୰ ࡢ Ỉ IUHHZDWHU ࡀ ඃ ඛ ⓗ ࡟ ⵨ Ⓨ ࡋ ࡚ ࠸ ࡃ ࡇ ࡜ ࡀ ཎ ᅉ ࡜ ᛮ ࢃ ࢀ ࡿ ࠋ ࡯ ࠿ ࡟ ࡶ ࠊ ⁽႞ ࡢ ෾ ᐖ ࡢ ᳨ ฟ ࢆ ព ㆑ ࡋ ࡓ ᐊ ෆ ᐇ 㦂 ࡟ ࡶ ᡂ ຌ ࡋ ࡓ㸦 ✵ 㝽 Ỉ ࡢ ෾ ⤖ ⭾ ᙇ ࡟ ࡼ ࡿ ✵ 㝽 ࢧ ࢖ ࢬࡢ ቑ ኱ ࢆ 7್ ࡢ ୖ ᪼ ࡜ ࡋ ࡚ ᳨ ฟ ࡛ ࡁ ࡓ 㸧>@ࠋࡇ ࡢ ࡼ ࠺ ࡟ ∦ ഃ 㛤 ᨺ ᆺ 105࡟ ࡼ ࡿ 㠀 ◚ ቯ ⾲㠃ࢫ࢟ࣕࢽࣥࢢࡢ⁽႞⣔ᘓ⠏≀ࡢ࣓ࣥࢸࢼࣥࢫ࡬ࡢ᭷ຠᛶࡀ☜ㄆ࡛ࡁࡓࠋ∦ ഃ 㛤 ᨺ ᆺ 105ࡣ ࠊᘓ ⠏࣭ᅵ ᮌ ࡟ 㝈 ࡽ ࡎ 㣗 ရ >@࡞ ࡝ ⌧ ሙ ࡛ ࡢ 㠀 ◚ ቯ࣭㠀 ౵ く ィࡀồࡵ ࡽ ࢀ ࡿ ௚ ࡢ ศ 㔝 ࡟ ࡶ ᗈ ࡃ ᛂ ⏝ ࡀ ᮇ ᚅ ࡛ ࡁ ࡿ ࠋ ∦ ഃ 㛤 ᨺ ᆺ 105ࡢ ே ⓗ ஺ ὶ ࢿ ࢵ ࢺ ࣡ ࣮ ࢡࢆ ❧ ࡕ ୖ ࡆ ࡓ ࡢ ࡛ >@ࠊ ࡇ ࡢ ศ 㔝 ࡟ ⯆ ࿡ ࠶ ࡿ ே ࡢ ཧ ධ ࢆ Ḽ ㏄ ࡋ ࡓ ࠸ ࠋ )LJ0RQLWRULQJRIDGU\LQJSODVWHUSODWHVDPSOHLQDODERUDWRU\ D 6QDSVKRW
7KHVDPHVHQVRUXQLWDV)LJZDVXVHG E ([DPSOHVRIWKHREWDLQHG&30*GDWD
5HIHUHQFHV>@<1DNDVKLPD  -SQ-$SSO3K\V VXEPLWWHG  
>@<1DNDVKLPDDQG16KLED  ,QW-)RRG3URS
>@105ࢽ ࣗ ࣮ ࢫ ࣞ ࢱ ࣮ ྕ 㸦 ᖺ ᭶ ᪥ 㸧 ࠙ ∦ ഃ 105ྠ ዲ ఍ ࡬ ࡢ ࠾ ㄏ ࠸ ࠚ
KWWSVZZZQPUMMSSGIQOBBSGI

－ 141 －

P6Y

XᰁⰍయ୙άᛶ໬࡟㛵୚ࡍࡿXist-SHARP」ྜయࡢ┦஫స⏝ゎᯒ‫ۑ‬㛗㇂ᕝᣅ▮㸪ᰗἑ⪔ኴ 㕥ᮌᣅᕭ ୰ᓥᘯ⛥ỌỤᓠᖾ㟷ᒣὒྐ୕ᓥṇつᆏᮏὈ୍
1༓ⴥᕤᴗ኱Ꮫ ඛ㐍ᕤᏛ◊✲⛉2ᮾி㒔❧኱Ꮫ㝔 ⌮Ꮫ㒊3ᮾி⸆⛉኱Ꮫ ⸆Ꮫ㒊

Interaction analysis of the Xist-SHARP complex involved in X chromosome inactivation‫ۑ‬Takuya Hasegawa1, Kota Yanagisawa1, Takumi Suzuki2, Hiroki Nakajima2, Takayuki Nagae3, Hiroshi
Aoyama3, Masaki Mishima2,3, Taiichi Sakamoto1
1

Faculty of Advanced Engineering, Chiba institute of technology

2 Graduate School, School of science, Tokyo Metropolitan University
3

School of Pharmacy, Tokyo University of Pharmacy and Life Science
X-Chromosome Inactivation (XCI) in human is known to compensate for the difference in gene

expression between female and male and requires a long non-coding RNA called X inactivation specifictranscript (Xist) RNA. Xist RNA has six repeat regions (A~F) in its 17 kb sequence and A repeat region isthought to be recognized SMRT/HDAC-associated repressor-protein (SHARP). Previously, some NMR
analyses of SHARP or the A repeat of Xist RNA have been performed, but the detail of the interaction
between Xist RNA and SHARP are unknown. In this study, we are trying to reveal the interaction using
NMR.
ࣄࢺࡣ㸪⏨ᛶ࡞ࡽXY㸪ዪᛶ࡞ࡽXXࡢ⤌ࡳྜࢃࡏࡢ
ᛶᰁⰍయࢆᣢࡗ࡚࠸ࡿ㸬ࡑࢀࡒࢀࡢᛶᰁⰍయࡢ㑇ఏᏊ㔞࡜ࡋ࡚ࡣ㸪XᰁⰍయࡀ1000ಶ⛬ᗘ࡟ᑐࡋ࡚㸪YᰁⰍయࡀ50ಶ⛬ᗘ࡛࠶ࡿ㸬ࡑࡢࡓࡵ㸪⏨ዪ㛫࡛㑇ఏᏊ㔞ࡢᕪࡀ⏕ࡌࡿ㸬ࡇࡢ㑇ఏᏊ㔞ࡢᕪࢆ⿵ൾࡍࡿࡓࡵ
࡟㸪ዪᛶࡢXXࡢ࠺ࡕ୍᪉ࡢXᰁⰍయࢆ୙άᛶ໬ࡍࡿ
ᶵᵓ࡜ࡋ࡚XᰁⰍయ୙άᛶ໬ࡀᏑᅾࡍࡿ㸬ࡑࡋ࡚㸪ࡇࡢ ᶵ ᵓ ࡟ 㛵 ୚ ࡍ ࡿ long non-coding RNA ࡜ ࡋ ࡚ X
inactive specific transcript RNA (Xist) RNAࡀ᫂ࡽ࠿࡟

Fig. 1 A-repeat region of Xist RNA࡞ࡗ࡚࠸ࡿ㸬Xist RNAࡣ㸪17kbࡢ㓄ิ୰࡟6ࡘࡢrepeat㡿ᇦ(A~F)ࢆᣢࡗ࡚࠸ࡿ㸬ࡑࡢ࠺ࡕ㸪A repeat㡿ᇦ࡟SMRT/HDAC-associated repressor-protein (SHARP)ࢱࣥࣃࢡ㉁ࡀ⤖ྜࡍࡿࡇ࡜ࡀ᫂ࡽ࠿࡟࡞
ࡗ࡚࠸ࡿ (Fig. 1)㸬SHARPࢱࣥࣃࢡ㉁ࡣ㸪Nᮎ➃ࡢRNA⤖ྜࣔࢳ࣮ࣇ࡜Cᮎ➃ࡢSpen paralog andortholog C-terminal (SPOC)ࢻ࣓࢖ࣥࡼࡾᵓᡂࡉࢀ࡚࠾ࡾ㸪SPOCࢻ࣓࢖ࣥ࡟ࡘ࠸࡚ࡣ୕ᓥࡽ࡟ࡼࡗ
࡚❧యᵓ㐀ࡀሗ࿌ࡉࢀ࡚࠸ࡿ1)㸬ࡲࡓ㸪Duszczykࡽ࡟ࡼࡗ࡚㸪Xist RNAࡢA repeat㡿ᇦࡢNMRゎᯒࡀ⾜ࢃࢀ㸪A repeat㡿ᇦࡀከ㔞య໬ࡍࡿࣔࢹࣝࡀሗ࿌ࡉࢀ࡚࠸ࡿ2)㸬ࡋ࠿ࡋ㸪Xist RNA࡜SHARPࢱ
ࣥࣃࢡ㉁ࡢ」ྜయࡢᙧᡂᶵᵓࡣ᫂ࡽ࠿࡟࡞ࡗ࡚࠸࡞࠸㸬ࡑࡇ࡛ᮏ◊✲࡛ࡣ㸪 NMRࢆ⏝࠸࡚
Xist-SHARP」ྜయࡢᙧᡂᶵᵓࢆゎ᫂ࡍࡿࡇ࡜ࢆ┠ⓗ࡟ࡋ࡚࠸ࡿ㸬
Xist RNA㸪SHARP ࢱࣥࣃࢡ㉁㸪⁐ᾮNMR‫ࡸࡃࡓ ࢃࡀࡏࡣۑ‬㸪ࡸ࡞ࡂࡉࢃ ࡇ࠺ࡓ, ࡍࡎࡁࡓࡃࡳ, ࡞࠿ࡌࡲ ࡦࢁࡁ, ࡞ࡀ࠼ ࡓ࠿ࡺࡁ, ࠶࠾ࡸࡲ ࡦࢁࡋ, ࡳࡋࡲ ࡲࡉࡁ, ࡉ࠿ࡶ࡜ ࡓ࠸࠸ࡕ－ 142 －

࠙᪉ἲࠚᮏ◊✲࡛ࡣ㸪A repeat㡿ᇦෆࡢ୍㒊ࢆXist_29࡜ࡋ࡚NMRゎᯒ࡟⏝࠸ࡓ(Fig.2)㸬ࡲࡓ㸪Xist_29࡟ྵࡲࢀࡿ2ࡘࡢstem loopࡢ࠺ࡕ㸪5͛ᮎ➃ഃࢆXist_loop1㸪3͛ᮎ➃ഃࢆXist_loop2࡜ࡋ࡚⏝࠸ࡓ㸬
Xist_29࡟ࡘ࠸࡚ࡣ㸪T7 RNA polymeraseࢆ⏝࠸ࡓヨ㦂⟶ෆ㌿෗ἲ࡛ㄪ〇ࡋ㸪࣏ࣜ࢔ࢡࣜࣝ࢔࣑ࢻ
ࢤࣝ㟁ẼὋື࡟ࡼࡾ⢭〇ࡋࡓ㸬Xist_29ࢆ13C࡜15N࡛ᶆ㆑ࡋࡓヨᩱ࡟ࡘ࠸࡚ࡶྠᵝ࡟ㄪ〇ࡋࡓ㸬
A8, G11, A21࠾ࡼࡧA23ࢆṧᇶ≉␗ⓗ࡟Ᏻᐃྠ఩యᶆ㆑ࡋࡓXist_29࡟ࡘ࠸࡚㸪኱㝧᪥㓟♫࡟ጤクྜᡂࡋࡓ㸬ࡲࡓ㸪Xist_loop1࠾ࡼࡧXist_loop2࡟ࡘ࠸࡚ࡣ㸪໭ᾏ㐨ࢩࢫࢸ࣒ࢧ࢖࢚ࣥࢫ♫࡟ጤクྜᡂࡋࡓ㸬 ᐃ⏝ࡢ⁐፹࡟ࡘ࠸࡚ࡣ㸪㝈⏺ࢁ㐣⭷(Sartorius♫)ࢆ⏝࠸࡚20 mM ࣜࣥ㓟ࢼࢺ࣒ࣜ࢘⦆
⾪ᾮ(pH6.5)࡟஺᥮ࡋࡓ㸬 ᐃ࡟ࡣ㸪AVANCE600 NMR ศගィ(Bruker Biospin♫)ࢆ⏝࠸ࡓ㸬࠙⤖ᯝ࠾ࡼࡧ⪃ᐹࠚึࡵ࡟㸪Xist_29㸪Xist_loop1 ࠾ࡼࡧ Xist_loop2 ࡟ࡘ࠸࡚㍍Ỉ୰࡛ࡢ NMR

ᐃࢆ⾜࠸㸪NOESY ࢫ࣌ࢡࢺࣝࢆ⏝࠸࡚࢖࣑ࣀࣉࣟࢺࣥࢩࢢࢼࣝࢆᖐᒓࡋࡓ㸬ࡑࡢ⤖ᯝ Xist_29 ࡛ࡣ㸪G19 ࡜ U26 ࡢ࢖࣑ࣀࣉࣟࢺࣥࡢ㛫࡟≉ᚩⓗ࡞ᙉ࠸ NOE ࡀほ ࡉࢀ, C5:G12㸪C6:G13㸪
C7:G14 ࠾ࡼࡧ C18:G27㸪G20:C25 ࡀࢫࢸ࣒ࢆᙧᡂࡋ࡚
࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬ࡉࡽ࡟ Xist_loop1 ࡛ࡣ㸪
C5:G12㸪C6:G13㸪C7:G14 ࡀࢫࢸ࣒ࢆᙧᡂࡋ࡚࠸ࡿࡇ
࡜ࡀ♧၀ࡉࢀࡓ㸬ࡲࡓ㸪Xist_loop2 ࡛ࡣ㸪 C18:G27㸪

Xist_29

G19:U26㸪G20:C25 ࡀࢫࢸ࣒ࢆᙧᡂࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬ḟ࡟㔜Ỉ୰࡛ࡢ NMR

ᐃࢆ⾜࠸㸪
Xist_29 ࡢ NOESYࢫ࣌ࢡࢺࣝࢆ⏝࠸࡚ H8, H6, H5 ࠾ࡼࡧ H1ƍࡢࢩࢢࢼࣝ
ࡢ㐃㙐ᖐᒓࢆヨࡳࡓ㸬ࡲࡓ㸪A8, G11, A21 ࠾ࡼࡧ A23ࢆṧᇶ≉␗ⓗ࡟Ᏻᐃྠ఩యᶆ㆑ࡋࡓヨᩱࢆ⏝࠸࡚㸪H8,
H6, H5 ࠾ࡼࡧ H1ƍࡢࢩࢢࢼࣝࡢᖐᒓࢆ㐍ࡵࡓࡀ㸪୍㒊ࡢࢩࢢࢼࣝࡀࣈ࣮ࣟࢻࢽࣥࢢࡋ࡚ࡋࡲ࠸㸪඲ṧᇶࡢᖐᒓ ࡀ ᅔ 㞴 ࡛ ࠶ ࡗ ࡓ 㸬 ࡑ ࡇ ࡛ 㸪 Xist_29 ࢆ ศ ๭ ࡋ ࡓ
Xist_loop1 ࠾ࡼࡧ Xist_loop2 ࡢ NOESY ࢫ࣌ࢡࢺࣝࡢ
㐃㙐ᖐᒓࢆ⾜ࡗࡓ㸬ࡑࡢ⤖ᯝ㸪Xist_loop1 ࡣ G12 ௨እࡢṧᇶࡢ H8, H6, H5 ࠾ࡼࡧ H1ƍࡢࢩࢢࢼࣝࢆᖐᒓࡍࡿ
ࡇ࡜ࡀ࡛ࡁ㸪A8 ࡢ H2 ࡜ G12 ࡢ H1ƍࡢ㛫࡟ NOE ࢩࢢ

Xist_loop1

Xist_loop2

Fig. 2 Secondary structuresof Xist_29, Xist_loop1, and
Xist_loop2

ࢼࣝࡀほ ࡉࢀࡓ㸬ࡇࡢࡇ࡜࠿ࡽ㸪Xist_loop1 ࡢ A8 ࡜ G12 ࡢሷᇶࡀࢫࢱࢵ࢟ࣥࢢࡋ࡚࠸ࡿࡇ࡜
ࡀ♧၀ࡉࢀࡓ㸬ࡲࡓ㸪Xist_loop2 ࡣ඲ṧᇶࢆᖐᒓࡍࡿࡇ࡜ࡀ࡛ࡁࡓ㸬 ⌧ᅾ㸪Xist ࡜ SHARP ࡢ┦஫స⏝࡟ࡘ࠸࡚㸪ゎᯒࢆ⾜ࡗ࡚࠸ࡿ㸬ཧ⪃ᩥ⊩1) Mikami S., et al., Structure 22: 35–46 (2014).
2) Duszczyk M.M., et al., RNA 17: 1973–1982 (2011).

－ 143 －

P7

㧗⢭ᗘࣜࣥࢠࣥࢢホ౯᪉ἲࡢ㛤Ⓨ‫ۑ‬ᒣᮏ⯟㍤㸪ࢺࣜࢺ࣮ࣛ࢝ࣥ ࢸࢩࢵࢺ㸪㧗ᶫ㞞ே2㸪ᒸᮧဴ⮳1ᮾிᕤᴗ኱Ꮫ ᕤᏛ㝔 ᶵᲔ⣔2⌮໬Ꮫ◊✲ᡤ ⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮Development of evaluation method on ringing‫ۑ‬Kouki Yamamoto1, Techit Tritrakarn1, Masato Takahashi2, Tetsuji Okamura1
1

Department of Mechanical Engineering, Tokyo Institute of Technology

2

Laboratory for NMR Engineering and Structural Science, RIKEN Center for Biosystems Dynamics Research“Ringing” is still one of the large problems in FT-NMR to observe quadrupolar or lowJ nuclei in solid-

state NMR. Not only such measurements but also large RF coils in MRI or RF coils with high quality factors,
such as High-Temperature Superconducting (HTS) RF coils, suffer from ringing. Some devices such as a Q
switch or some special pulse sequences have been developed to shorten “dead time”. However, this problem
still has been unsolved. We have developed the evaluation methodology to analyze the origin of ringing using
our home-build spectrometer. This method can observe the ringing that looks like an NMR signal and whichpart makes ringing in the circuit to improve NMR probes and spectrometers.
NMR/MRI ⿦⨨㛤Ⓨ࡟࠾ࡅࡿㄢ㢟ࡢ 1 ࡘ࡟ࣜࣥࢠࣥࢢࡀ࠶ࡿࠋࣜࣥࢠࣥࢢࡣ RF ࣃࣝࢫࡢ㏦ಙ࡜ྠ᫬࡟⏕ࡌࠊ⮬⏤᣺ືῶ⾶(FID)࡟ṍࡳࢆ⏕ࡌࡉࡏ NMR ಙྕࢆ୙᫂░࡟ࡍࡿ࢔࣮ࢸ࢕ࣇ࢓ࢡࢺ࡛
࠶ࡿࠋ୍⯡࡟ࣜࣥࢠࣥࢢࡀῶ⾶ࡋᾘ⁛ࡍࡿࡲ࡛ࡢ᫬㛫ࢆࢹࢵࢻࢱ࢖࣒(୙ឤ᫬㛫)࡜ࡋ࡚ᑐ⟇ࢆ࠾⾜࠺ࡀࠊࡑࡢ㛗ࡉศࡢಙྕᙉᗘࡀపୗࡍࡿࠋࢫࣆ࢚ࣥࢥ࣮ࢆ⏝࠸ࡿ࡜ࡋ࡚ࡶྍ⬟࡞㝈ࡾࢹࢵࢻࢱ
࢖࣒ࡣ▷࠸ࡇ࡜ࡀᮃࡲࡋ࠸ࠋᅛయ NMR ࡛ࡢᅄᴟᏊ᰾ࡸప࿘Ἴ᰾ࠊపኳ↛Ꮡᅾẚ࡛ಙྕᙉᗘࡀᑠ
ࡉ࠸ሙྜࠊMRI ࡢࡼ࠺࡞኱ᆺࡢ RF ࢥ࢖ࣝࠊ㧗 ㉸ఏᑟ RF ࢥ࢖ࣝࡢࡼ࠺࡟ Q ್ࡀ㧗࠸ሙྜ࡞࡝
࡛ࢹࢵࢻࢱ࢖࣒ࡀ㛗ࡃ࡞ࡾࠊ⦆࿴᫬㛫࡜ྠ➼࡟࡞ࡗ࡚ࡋࡲ࠺ࡓࡵࡇࡢၥ㢟࡟┤㠃ࡋࡸࡍ࠸ࠋ
ࢹࢵࢻࢱ࢖࣒▷⦰ࡢࡓࡵࡢ◊✲࡛ࡣࠊࡇࢀࡲ࡛࡟ Q ࢫ࢖ࢵࢳࡸྜᡂࣃࣝࢫࢩ࣮ࢣࣥࢫࡀ୺࡟ᥦ
᱌ࡉࢀ࡚࠸ࡿࠋQ ࢫ࢖ࢵࢳࡣ୍᫬ⓗ࡟ Q ್ࢆపῶࡉࡏࣉ࣮ࣟࣈࡢࣜࣥࢠࣥࢢ࢚ࢿࣝࢠ࣮ࢆຠ⋡ⓗ࡟ῶ⾶ࡉࡏࡿࡇ࡜ࡀ࡛ࡁࡿࡀࠊࣉ࣮ࣟࣈእ࡛Ⓨ⏕ࡋࡓࣜࣥࢠࣥࢢ࡬ࡢᑐฎࡀ࡛ࡁ࡞࠸ࡇ࡜ࡸࠊ୍
⯡ⓗ࡟࢔ࢡࢸ࢕ࣈ⣲Ꮚࡀ౑⏝ࡉࢀࡿࡓࡵࠊษࡾ᭰࠼᫬ࡢ㐣Ώຠᯝ࡟ࡼࡾ෌ࡧࣜࣥࢠࣥࢢࡀ⏕ࡌࡿྍ⬟ᛶࡀ࠶ࡿࡇ࡜࡬ࡢᠱᛕࡀ࠶ࡿࠋࡲࡓࠊྜᡂࣃࣝࢫࢩ࣮ࢣࣥࢫࡣᩘᏛⓗᡭἲ࡟ࡼࡾ FID ࠿ࡽࣜࣥࢠࣥࢢࢆῶ⟬ࡍࡿ≺࠸ࡀ࠶ࡿࡀࠊGerothanassis1 ࡟ࡼࡿ࡜ࠊ࢔ࢥ࣮ࢫࢸ࢕ࢵࢡࣜࣥࢠࣥࢢࡢ≉ᛶࡣ␗࡞ࡿࣇࣜࢵࣉゅ࡟ᑐࡋ୍࡚ᐃ࡛࡞࠸ࡓࡵࠊࢫࣆ࢚ࣥࢥ࣮࡜ࡢే⏝ࡀ࡛ࡁ࡞࠸ࠋᅛయᅄᴟᏊ᰾
ࡢ᳨ฟ࡟ࡣࣁ࣮ࢻ࢙࢘࢔㠃࡛ࡢࣜࣥࢠࣥࢢᑐ⟇ࡀ⌮᝿ⓗ࡛࠶ࡿࠋᮏ◊✲࡛ࡣࠊࣜࣥࢠࣥࢢࢆホ౯ࡍࡿ⿦⨨࡜ࡋ࡚⮬సࡢNMRศගィࢆ⏝࠸ࡓࠋࢼࢩࣙࢼࣝ࢖ࣥ
ࢫࢶ࣓ࣝࣥࢶ♫〇ࡢUSRP-2920㸦Software-Defined Radio(SDR)࡜࿧ࡤࢀࡿࠊࡇࢀࡲ࡛ࣁ࣮ࢻ࢙࢘
࢔࡛ᐇ⌧ࡉࢀ࡚ࡁࡓᶵ⬟ࢆࢯࣇࢺ࢙࢘࢔࡛ᐇ⌧ࡍࡿ⿦⨨㸧࡛࠶ࡿࠋࡇࡢ⿦⨨ࢆไᚚࡍࡿࢯࣇࢺ࢘
࢙࢔ࢆࢼࢩࣙࢼࣝ࢖ࣥࢫࢶ࣓ࣝࣥࢶ♫〇ࡢLabVIEW࡜NI-USRP࡛⮬సࡋࡓࠋࡇࢀ࡟ࡼࡾᰂ㌾࡟௵ពࡢ᫬้ࡢಙྕࢆ ᐃࡍࡿࡇ࡜ࡀ࡛ࡁࠊࡲࡓ㏻ᖖࡢศගィ࡛ࡣ⾜࠼࡞࠸ࡼ࠺࡞సືࡢࡉࡏ᪉ࡶྍ
ࣜࣥࢠࣥࢢ, 㧗 ㉸ఏᑟRFࢥ࢖ࣝ㸪ᅄᴟᏊ᰾‫ࡁ࠺ࡇ࡜ࡶࡲࡸۑ‬㸪࡜ࡾ࡜ࡽ࠿࣮ࢇ࡚ࡋࡗ࡜㸪ࡓ࠿ࡣࡋࡲࡉ࡜㸪࠾࠿ࡴࡽ࡚ࡘࡌ

－ 144 －

⬟࡛࠶ࡿࠋࣃ࣮࣡࢔ࣥࣉ࡟ࡣࣈࣝ࢝
࣮♫〇ࡢࡶࡢࢆ౑⏝ࡋࠊLNA ࡟ࡣ࣑ࢽࢧ࣮࢟ࢵࢺ♫ࡢ ZKL-1R5 ࢆ⏝࠸

6SHFWURPHWHU
7[ࡓࠋᚑ᮶ࣜࣥࢠࣥࢢࡢホ౯᪉ἲ࡜ࡋ

'87

/1$
'XSOH[HU

3RZHU$PSOLILHU

6SHFWURPHWHU
5[

: ORDG

࡚ࡣࠊບ㉳ࣃࣝࢫࡸࣜࣥࢠࣥࢢಙྕ

Fig. 1. Schematic of the evaluation circuit.

ࢆ࢜ࢩࣟࢫࢥ࣮ࣉ࡛ほᐹࡋ࡚࠸ࡓ

The ringing intensity generated by DUT(Device Under Test)ࡀࠊ࢜ࢩࣟࢫࢥ࣮ࣉ࡛ࡣᐇ㝿ࡢ NMR

was investigated using our home-built spectrometer.

ಙྕࡢࡼ࠺࡞ᚤᙅ࡞ಙྕࢆほᐹࡍࡿ࡟ࡣ୙ྥࡁ࡛࠶ࡿࠋ୍᪉ࠊᮏ◊✲࡛⏝࠸ࡓ⮬సศගィ࡛ࡣࠊࣜࣥࢠࣥࢢࡀ
Ⓨ⏕ࡋ࡚࠿ࡽῶ⾶ࡋ࡚ᚤᙅ࡞ NMR

Absolute value
Ceramic
capacitorಙྕ࡜ྠ➼ࣞ࣋ࣝ࡟࡞ࡿࡲ࡛㐃⥆ⓗ࡟ほࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡇࡢ฼Ⅼ

Mica
capacitorࢆά࠿ࡋ࡚ࠊࣜࣥࢠࣥࢢࡢⓎ⏕※ࢆ≉ᐃࡍࡿᐇ㦂ࢆ⾜ࡗࡓࠋNo
DUTࡇࢀࡲ࡛ࡢᐇ㦂࠿ࡽࣜࣥࢠࣥࢢࡣ
ࣉ࣮ࣟࣈෆ㒊࡛᭱ࡶከࡃⓎ⏕ࡍࡿ

400ࡀࠊࣜࣥࢠࣥࢢࡢⓎ⏕※ࡣከᒱ࡟Ώ
ࡿࡇ࡜ࡀࢃ࠿ࡗ࡚࠸ࡿࠋࣜࣥࢠࣥࢢ
ࢆṇ☜࡟ᐃࡍࡿࡓࡵ࡟ࡣࠊࡣࡌࡵ

࡟ࣉ࣮ࣟࣈ௨እࡢᙳ㡪ࢆ᭱ᑠ㝈࡟ࡍࡿᚲせࡀ࠶ࡿࠋࡑࡇ࡛ࠊࣉ࣮ࣟࣈࡢ௦

200
0
-200
Frequency [kHz]-400

Fig. 2. FT spectra of ringing with DUT.
The applied RF pulse was 58 MHz, 100 W, 100 s. 4096
transients were recorded and left shift before FT was 15 s.

ࢃࡾ࡟ 50 Ȑ⤊➃᢬ᢠࢆ⏝࠸࡚ࣉ࣮ࣟࣈእࡢⓎ⏕※ࢆ᳨ウࡋᑐ⟇ࡍࡿᡭἲࢆᥦ᱌ࡍࡿࠋᐇ㦂ࡣ Fig.
1 ࡟♧ࡍᅇ㊰ࢆ⏝࠸࡚⾜ࡗࡓࠋ௒ᅇࡢ DUT(Device Under Test)ࡣ RF ࣃࣝࢫࡢ࿘Ἴᩘ࡛ඹ᣺ࡍࡿ┤ิඹ᣺ᅇ㊰࡛࠶ࡾࠊᤄධᦆኻࡣ-0.3 dB ⛬ᗘ࡛࠶ࡿࠋDUT ࢆᤄධࡋ࡞࠸ሙྜࢆᇶ‽࡜ࡋࠊDUT ࡢᤄධ࡟ࡼࡿኚ໬࡟ࡘ࠸࡚ࠊࢭ࣑ࣛࢵࢡࢥࣥࢹࣥࢧ(Knowles Syfer MLCC ࢩ࣮ࣜࢬ)ࠊ࣐࢖࢝ࢥࣥࢹ
ࣥࢧ(Cornell Dubilier CM ࢩ࣮ࣜࢬ)ࡢ 2 ✀㢮ࢆ⏝࠸࡚ẚ㍑ᐇ㦂ࢆ⾜ࡗࡓࠋᐇ㦂࡛ᚓࡽࢀࡓࣜࣥࢠࣥࢢࡢࣇ࣮࢚ࣜኚ᥮ࢫ࣌ࢡࢺࣝ㸦⤯ᑐ್⾲グ㸧ࢆ Fig. 2 ࡟♧ࡍࠋRF ࣃࣝࢫࡣ 57.91 MHz, 100 W, 100 sࠊ✚⟬ᅇᩘࡣ 4096 ᅇ࡛࠶ࡿࠋࣇ࣮࢚ࣜኚ᥮ᚋࡢ⤖ᯝࢆẚ㍑ࡋࡸࡍࡃࡍࡿࡓࡵ࡟᭱ึࡢ 15 s ࡢಙྕࡣ๐㝖ࡋࡓࠋ✚⟬ᅇᩘࢆቑࡸࡉ࡞࠸࡜ࢃ࠿ࡽ࡞࠸ᙉᗘ࡛࠶ࡿࡀࠊ
ࢭ࣑ࣛࢵࢡࢥࣥࢹࣥࢧ࡛᫂☜࡟ࣜࣥࢠࣥࢢࡀቑຍࡋࡓࠋ࣐࢖࢝ࢥࣥࢹࣥࢧ࡛ࡣⓎ⏕ࡋ࡞࠸ࡇ࡜࠿
ࡽࠊ౑⏝ࡋ࡚࠸ࡿࢭ࣑ࣛࢵࢡᮦᩱࡀཎᅉ࡛࠶ࡿ࡜ண᝿࡛ࡁࡿࠋከ⤖ᬗᙉㄏ㟁ᛶࢭ࣑ࣛࢵࢡࡣࣆ࢚
ࢰຠᯝ㸦ᅽ㟁ຠᯝ㸧ࢆᣢࡘࡓࡵࠊRF ࣃࣝࢫࡢ㧗㟁ᅽࡀࢥࣥࢹࣥࢧෆ࡛ᶵᲔ᣺ື࡟ኚ᥮ࡉࢀ࡚࠸ࡿ
࡜⪃࠼࡚࠸ࡿࠋNMR/MRI ࡛ࡣᙉຊ࡞ RF ࣃࣝࢫࢆ⏝࠸ࠊ࠿ࡘ┤ᚋࡢᚤᙅ࡞ಙྕࢆ ᐃࡍࡿࠋࣆ࢚
ࢰຠᯝ࡟ࡘ࠸࡚ࡣ࠶ࡿ⛬ᗘࢭ࣑ࣛࢵࢡࢥࣥࢹࣥࢧ࣓࣮࣮࢝ࡶᑐ⟇ࡋ࡚࠸ࡿ࡜᝿ീ࡛ࡁࡿࡀࠊ᝿ᐃ
ࢆ㉸࠼࡚࠸ࡿ౑࠸᪉࡟࡞ࡗ࡚࠸ࡿྍ⬟ᛶࡀ࠶ࡿࠋ
References(1) I. P. Gerothanassis, Methods Of Avoiding The Effects Of Acoustic Ringing In Pulsed Fourier Transform
Nuclear Magnetic Resonance Spectroscopy, Progress in nuclear magnetic resonance spectroscopy. Vol. 19,(1987) 267-329－ 145 －

P8Y

Double nutation cross polarization‫⋤ۑ‬㞵㸪Ṋ⏣࿴⾜1ி㒔኱Ꮫ኱Ꮫ㝔⌮Ꮫ◊✲⛉໬Ꮫᑓᨷ‫ۑ‬Yu Wang1, Kazuyuki Takeda1
1

Division of Chemistry, Graduate School of Science, Kyoto University

We propose a method for cross polarization (CP) dedicated for low-ߛ spins, in which double nutation(DONUT) applied at the source, high-ߛ spins leads to the Hartmann-Hahn condition well suited for thelimited nutation rate of the target spins, while the spin-locking field is retained high enough.
Introduction
Cross polarization (CP) is widely used to transfer polarization from one spin species, ‫ܫ‬, to another, ܵ, andthereby to enhance the magnetization of the latter. In CP, resonant rf fields are applied to both ‫ ܫ‬and ܵ withsuch intensities ‫ܤ‬ଵூ and ‫ܤ‬ଵௌ that satisfy the Hartmann-Hahn condition[1] given by ߛூ ‫ܤ‬ଵூ ൌ ߛௌ ‫ܤ‬ଵௌ ൅݊߱௥ ሺ݊ ൌ േͳǡ േʹሻ , where ߛூ and ߛௌ are the gyromagnetic ratios and ߱௥ is the spinning speed. The
condition indicates that the smaller ߛௌ is, the higher ‫ܤ‬ଵௌ needs to be. However, application of high rf power
is often undesirable. Then, one needs to reduce ‫ܤ‬ଵூ , paying the price of inefficient spin-locking in thepresence of strong homonuclear dipolar interactions among spins ‫ܫ‬. A challenge in polarization transfer fromthe abundent spins to low-ߛ spins arises from these incompatible requirements.
CP using time-averaged precession frequency (CP-TAPF)[2] is one elegant solution realizing reduced
nutation speed while keeping the spin-locking field high enough. However, CP-TAPF involves repetitions ofabrupt inversion of the phase of the rf irradiation, which may cause significant dephasing of the magnetization.
In this work, we propose an alternative CP method dedicated for the low-ߛ spins, employing the smooth rf
modulation that allows both slow nutation of spins ܵ and high-enough spin-locking field realized throughdouble nutation (DONUT)[3], i.e., simultaneous nutations around two separate axes.
Principles

߱ଵௌ

DONUT around, say, the ‫ ݔ‬and the ‫ ݖ‬axes, with nutation
rates ߱ଵ and ߱ଶ is described by a propagator ܷሺ‫ݐ‬ሻ ൌሺെ݅߱ଵ ‫ܫݐ‬௫ ሻ ሺെ݅߱ଶ ‫ܫݐ‬௭ ሻ. In the interaction representation,the ‫ܫ‬௭ term of the dipolar interaction acquires time dependencewith the mixed frequencies ȭ ൌ ߱ଵ ൅ ߱ଶ and ȟ ൌ ߱ଵ െ ߱ଶ ,and is represented asܷ ିଵ ‫ܫ‬௭ ܷ ൌ ‫ܫ‬௭  ߱ଵ ‫ ݐ‬െ ൫‫ܫ‬ା ݁െ݅ȟ‫ ݐ‬൅‫݅݁ ିܫ‬ȟ‫ ݐ‬൯ȀͶ ൅ ൫‫ܫ‬ା ݁െ݅ȭ‫ ݐ‬൅ ‫݅݁ ିܫ‬ȭ‫ݐ‬൯ȀͶ .

Undercontinuous

rf

irradiation at spins ܵ with a nutation frequency ߱ଵௌ , we obtainthe Hartmann-Hahn condition to be

Fig. 1. A pulse sequence for DONUT CP

߱ଵௌ ൌ ȭ ൅ ݊߱௥(1)߱ଵௌ ൌ ȁȟȁ ൅ ݊߱௥(2)
We found that the case of Eq. (2), ȁȟȁ, which is compatible with the requirement of the slow nutation rate
for spins ܵ, causes double-quantum exchange between ‫ ܫ‬and ܵ if ߱ଵ ൐ ߱ଶ . When the ‫ ݖ‬axis is chosen
Cross polarization (CP), Double nutation (DONUT), low-gamma nuclei‫ࢇ࠸ࢀ࠺࠾ۑ‬㸪ࡓࡅࡔ࠿ࡎࡺࡁ

－ 146 －

for the second-nutation axis, the ‫ܫ‬௭ magnetization islocked. Thus, unlike the conventional CP, the initialȁઢȁȀ૛࣊

ߨΤʹ pulse is not required. The rf Hamiltonian ‫ܪ‬઱Ȁ૛࣊that leads to ܷ is straightforwardly calculated as‫ ܪ‬ൌ ܷ݅ሶܷ ିଵ ൌ ߱ଵ ‫ܫ‬௫ ൅ ߱ଶ ሺ‫ܫ‬௭  ߱ଵ ‫ ݐ‬െ ‫ܫ‬௬  ߱ଵ ‫ݐ‬ሻ ,whence smooth modulations of the amplitude andphase are obtained to be ඥ߱ଵଶ ൅ ߱ଶଶ ଶ ሺ߱ଵ ‫ݐ‬ሻ andିଵ ሾെ߱ଶ ሺ߱ଵ ‫ݐ‬ሻΤ߱ଵ ሿ െ ߱ଶ ሺ߱ଵ ‫ݐ‬ሻΤ߱ଵ . The
pulse sequence for DONUT CP is depicted in Fig. 1.
Results and discussion
Fig. 2 shows߱ଵௌ

dependence of the13࣓࢘ Ȁ૛࣊

C

magnetization of adamantane under 1H-13C DONUT
CP. As expected, we observed the enhancement under
the conditions given in Eqs. (1) and (2). The negative
enhancementwithȁȟȁ ൅ ݊߱௥for߱ଵ ൐ ߱ଶ

confirms the double-quantum nature of polarization

Fig. 2. 1H-13C Hartmann-Hahn matching profiles
obtained with DONUT CP with rates (߱ଵ Τʹߨ ǡ ߱ଶ Τʹߨ )of (20 kHz, 50 kHz) (circles) and (50 kHz, 20 kHz)(squares) in 7 T under MAS at 9 kHz.

transfer, as we predicted theoretically.
With applications to low- ߛ nuclei in mind, we
1ሺઢ െ ࣓࢘ ሻȀ૛࣊

15

examined the performance of H- N DONUT CP in
15

N-labeled histidine for relatively low nutation rates

߱ଵௌ Τʹߨ ൏20 kHz. As demonstrated in Fig. 3, the 15N
magnetization was enhanced with the condition ȁȟȁ െ߱௥ by a factor of 8.8, close to the maximum possible
value given by ȁߛு Ȁߛே ȁ ~10, whereas CP-TAPF
resulted in the deviation of the optimal 15N nutation rate
and the smaller enhancement factor.
Summary
DONUT CP offers efficient polarization transferfrom the abundant to the low-ߛ nuclei.
Fig. 3. 1H-15N Hartmann-Hahn matching profiles
obtainedby
DONUT CP (squares)with(߱ଵ Τʹߨ ǡ ߱ଶ Τʹߨ ) of (68 kHz, 30 kHz) and CP-TAPF(triangles) with an average 1H nutation frequency of 38
kHz in polycrystalline 15N-labeled histidine in 9.4 T
under MAS at 23 kHz.

References[1] S. R. Hartmann, E. L. Hahn, Phys. Rev. 128 (1962) 2042-2053.
[2] K. Takegoshi, C. A. McDowell, J. Magn. Reson. 67 (1986) 356-361.
[3] K. Takeda, A. Wakisaka, K. Takegoshi, J. Chem. Phys. 141 (2014) 224202.

－ 147 －

P9

Presaturation pulseࢆ⏝࠸ࡓṇ☜࡞1H-qNMRࡢ᳨ウ‫ۑ‬ᩪ⸨┤ᶞ1ᅜ❧⎔ቃ◊✲ᡤ ⎔ቃࣜࢫࢡ࣭೺ᗣ㡿ᇦ ᇶ┙ィ ࢭࣥࢱ࣮Study on an accurate 1H-qNMR with a presaturation pulse‫ۑ‬Naoki Saito1
1Center for Environmental Standards and Measurement, Health and Environmental Risk Division, National

Institute for Environmental Studies
Presaturation (pre-SAT) remains widely in use since it is one of the simplest techniques having highrobustness in solvent suppressions. In the present work, accuracy of 1H-qNMR with pre-SAT was evaluatedand improved. Conventional pre-SAT decreased especially signal areas of analytes near an irradiated water
signal, allowing not to accurately determining concentration values of the analytes. The improved method isa fresh dual pre-SAT for analyzing H2O-rich samples using 1H-qNMR. The feature of the method is
performing another dummy irradiation with a suitable frequency in addition to the irradiation to the water
signal. The fresh dual pre-SAT was finally demonstrated using a 10 vol% D2O/H2O solution.
࠙1. ࡣࡌࡵ࡟ࠚ

㏆ᖺࠊ1H NMR࡟ࡼࡿᐃ㔞ศᯒἲ㸦௨ୗࠊ1H-qNMR㸧ࡢṇ☜ࡉྥୖ࡟క࠸ࠊ⏕యヨᩱࡸ㣗ရ࡞࡝ࠊከ㔞࡞㍍Ỉࢆྵࡴヨᩱࢆ⏝࠸ࡓNMR࣓ࢱ࣑࣎ࣟࢡࢫ◊✲ࡀࡲࡍࡲࡍቑຍࡋ࡚
࠸ࡿࠋࡇࢀࡽヨᩱࢆ ᐃࡍࡿ㝿࡟ࡣࠊ㍍Ỉࢩࢢࢼࣝࡢᾘཤࡢࡓࡵ࡟ࠊྂ඾ⓗ࡞Presaturation pulse㸦௨ୗࠊpre-SAT㸧ࡢ฼⏝ࢆࡣࡌࡵࠊpre-SATࢆే⏝ࡋࡓ1D-NOESYἲࠊWETἲ࡞࡝ࡀỗ⏝ࡉࢀ࡚࠸ࡿࠋ
ࡋ࠿ࡋࠊᚓࡽࢀࡿᐃ㔞್ࡢṇ☜ࡉ࡟ࡘ࠸࡚ࡣࠊᮍࡔ㆟ㄽࡉࢀࡿࡇ࡜ࡀᑡ࡞࠸[1-3]ࠋࡑࡇ࡛ࠊࡲࡎ
ࡣpre-SATࢆ⏝࠸ࡓᐃ㔞 ᐃࡢṇ☜ࡉࢆホ౯ࡍࡿ࡜ඹ࡟ࠊࡑࡢṇ☜ࡉྥୖࢆ᳨ウࡋࡓࠋ
࠙2. ᐇ㦂ࠚศᯒヨᩱ࡟ࡣL-ࣇ࢙ࢽࣝ࢔ࣛࢽࣥࠊL-ࣂࣜࣥࠊL-ࢢࣜࢩࣥࡢྛㄆドᶆ‽≀㉁㸦⏘⥲◊〇㸧ࡢ࡯࠿ࠊ࣐ࣞ࢖ࣥ㓟ㄆドᶆ‽≀㉁㸦ᐩኈࣇ࢖࣒ࣝ࿴ග⣧⸆〇㸧ࢆ⏝࠸ࡓࠋෆᶆ‽≀㉁࡟ࡣDSS-d6ㄆドᶆ‽≀㉁㸦ᐩኈࣇ࢖࣒ࣝ࿴ග⣧⸆〇㸧ࢆࠊ⁐፹࡟ࡣ㔜Ỉ㸦D2Oࠊ࢔࢖ࢯࢸࢵࢡ〇㸧࠾ࡼࡧ⣧Ỉ㸦H2O㸧ࢆ⏝࠸ࡓࠋヨᩱㄪ〇࡟ࡣ࣑ࢡࣟኳࡧࢇ࠾ࡼࡧࢭ࣑࣑ࢡࣟኳࡧࢇ㸦࣓ࢺ࣮࣭ࣛࢺ
ࣞࢻ〇㸧ࢆࠊ ᐃ࡟ࡣ5 mm FG/TH࣮࢜ࢺࢳ࣮ࣗࣥࣉ࣮ࣟࣈࢆഛ࠼ࡓ500 MHzࡢNMR⿦⨨㸦ECA500ࠊ
᪥ᮏ㟁Ꮚ〇㸧ࢆࠊゎᯒ࡟ࡣMnova ver.7.0.2࠾ࡼࡧver.14.1.2㸦MestreLab〇㸧ࢆ⏝࠸ࡓࠋࡲࡎࠊࣇ࢙ࢽࣝ࢔ࣛࢽࣥࠊࣂࣜࣥࡑࢀࡒࢀࡀ⁐ゎࡍࡿD2O⁐ᾮ㸦DSS-d6ῧຍ῭㸧ࢆヨᩱ⁐ᾮ࡜ࡋ࡚ࠊṧ␃Ỉ1Hࢩࢢࢼࣝ࡟pre-SAT↷ᑕࡋࠊศᯒᑐ㇟ᡂศࡢ⃰ᗘ ᐃ್࡟⏕ࡌࡿࣂ࢖࢔ࢫࢆホ౯ࡋࡓࠋḟ࡟ࠊࡇࡢࣂ࢖࢔ࢫࢆ᤼㝖࡛ࡁᚓࡿpre-SATࢹࣗ࢔ࣝ↷ᑕἲ㸦௨ୗࠊࢹࣗ࢔ࣝ↷ᑕἲ㸧ࢆ⪃᱌ࡋࠊྠ⁐ᾮࢆ⏝࠸࡚ṇ☜ࡉࢆホ౯ࡋࡓࠋࡑࡢᚋࠊࢢࣜࢩࣥ࡜࣐ࣞ࢖ࣥ㓟ࡢ୧⪅ࡀ⁐ゎࡍࡿ10 vol%D2O/H2O⁐ᾮ㸦DSS-d6ῧຍ῭㸧ࢆ⏝࠸࡚ࠊࢹࣗ࢔ࣝ↷ᑕἲࡢጇᙜᛶ☜ㄆヨ㦂ࢆ⾜ࡗࡓࠋ࡞࠾ࠊ ᐃࡣᐃ㔞 ᐃ᮲௳ [ ᐃ ᗘ25 ǀCࠊࣇࣜࢵࣉゅ90ǀࠊྲྀ㎸ࡳ᫬㛫4⛊ࠊࢫ࣌ࢡࢺࣝᖜ500 ppm㸦ࢹࢪࢱࣝࣇ࢕ࣝࢱ࡞ࡋ㸧ࠊ✚⟬ᅇᩘ8ᅇ࠶ࡿ࠸ࡣ32ᅇࠊ⧞㏉ࡋᚅࡕ᫬㛫60⛊࡞࡝] ࡛⾜ࡗࡓࠋ࠙3. ⤖ᯝ࡜⪃ᐹࠚ ṧ␃Ỉ1Hࢩࢢࢼࣝ࡬pre-SAT↷ᑕࡋࠊࣇ࢙ࢽࣝ࢔ࣛࢽࣥࠊࣂࣜࣥࡢD఩ࠊE఩ࠊ
J఩࠶ࡿ࠸ࡣࣇ࢙ࢽࣝᇶࡑࢀࡒࢀࡢ1Hࢩࢢࢼࣝࡼࡾ⃰ᗘ ᐃ್ࢆồࡵࡓ㸦Fig. 1a㸧ࠋࡑࡢ⤖ᯝࠊỈpresaturation, qNMR, ṇ☜ࡉࠐࡉ࠸࡜࠺࡞࠾ࡁ

－ 148 －

ࢩࢢࢼࣝ࠿ࡽࡢ໬Ꮫࢩࣇࢺᕪࡢ⤯ᑐ್ࡀᑠࡉ࠸ࢩࢢࢼࣝ࡯࡝ࠊ኱ࡁ࡞⃰ᗘపୗࢆ♧ࡋࡓࠋࡇࡢ⃰ᗘపୗࡣࠊpre-SAT↷ᑕฟຊࡢቑ኱࡟ࡼࡾຓ㛗ࡉࢀࠊ᭱኱48 %࡟⮳ࡗࡓ㸦Fig. 1c㸧ࠋỈࢩࢢࢼࣝ࠿
ࡽࡢ໬Ꮫࢩࣇࢺᕪࡢ⤯ᑐ್ࡀᑠࡉࡃ࡞ࡿ࡯࡝ࠊ࠿ࡘࠊpre-SAT↷ᑕฟຊࡀቑ኱ࡍࡿ࡯࡝ࠊෆᶆ‽≀㉁࡟ẚ࡭࡚ศᯒᑐ㇟ᡂศࡢࢩࢢࢼࣝ㠃✚పୗ⋡ࡀⴭࡋࡃቑ኱ࡍࡿࡓࡵ࡜⪃࠼ࡽࢀࡿࠋ
୍᪉ࠊ⪃᱌ࡋࡓࢹࣗ࢔ࣝ↷ᑕἲࡣࠊṧ␃Ỉ1Hࢩࢢࢼࣝ࡬ࡢpre-SAT↷ᑕ࡟ຍ࠼࡚ࠊศᯒᑐ㇟ᡂศ
ࡢࢩࢢࢼࣝࡈ࡜࡟㐺ࡋࡓ࿘Ἴᩘ࡛ࡢࢲ࣑࣮ࡢpre-SAT↷ᑕࡢྠ᫬ᐇ⾜ࢆ≉ᚩ࡜ࡍࡿ㸦Fig. 1b; D఩1Hࢩࢢࢼࣝࡢ౛࡛ࡣDࢆేグࡋࡓୗ▮༳㸧ࠋࡇࢀ࡟ࡼࡾศᯒᑐ㇟ᡂศ࡜ෆᶆ‽≀㉁࡜࡛ࠊpre-SAT↷ᑕ࡟ࡼࡿࢩࢢࢼࣝ㠃✚పୗࡀྠ➼໬ࠊ┦ẅࡉࢀࠊศᯒᑐ㇟ᡂศࡢ⃰ᗘᐃ್ࢆࡼࡾṇࡋࡃᚓࡿࡇ

࡜ࡀ࡛ࡁࡿࠋ౛࠼ࡤࠊࣇ࢙ࢽࣝ࢔ࣛࢽࣥࡢD఩1

Hࢩࢢࢼࣝࡢሙྜࠊ㏻ᖖࡢpre-SAT↷ᑕ࡛ࡣ᭱኱48 %ࡢ⃰ᗘపୗࡀㄆࡵࡽࢀࡓࡀࠊࢹࣗ࢔ࣝ↷ᑕ࡛ࡣ⃰ᗘపୗࢆ3 %௨ୗ࡟ᢚไ࡛ࡁࡓ㸦Fig. 1d㸧ࠋࢢࣜࢩࣥ㸦௨ୗࠊGly㸧࡜࣐ࣞ࢖ࣥ㓟㸦௨ୗࠊMA㸧ࡢ୧⪅ࡀ⁐ゎࡍࡿ10 vol% D2O/H2O⁐ᾮࢆ⏝࠸ࡓヨ㦂࡛ࡣࠊ㏻ᖖࡢpre-SAT↷ᑕ࡛ࡣGly㸸368.2s10.5㸦mg/kg㸧ࠊMA㸸456.4s16.0㸦mg/kg㸧࡜࡞ࡗࡓ࡜ࡇࢁࠊࢹࣗ࢔ࣝ↷ᑕ࡛ࡣGly㸸513.8s21.4㸦mg/kg㸧ࠊMA㸸512.4s25.9㸦mg/kg; ௨ୖࠊsᐃ್ࡀㄪ〇್㸦Gly㸸503.1 mg/kgࠊMA㸸506.9 mg/kg㸧࡜ ᐃࡤࡽࡘᶆ‽೫ᕪ2㸧࡜࡞ࡾࠊ⃰ᗘࡁࡢ⠊ᅖ୍࡛⮴ࡋࡓࠋࡇࢀ࡟ࡼࡾࠊ⪃᱌ࡋࡓࢹࣗ࢔ࣝ↷ᑕἲࡢጇᙜᛶࡀ☜ㄆࡉࢀࡓࠋ
a)

E

b)
phenyl

HOD

E

DSS-d6HOD

D E(D) (E

DSS-d6

J
D

D
HOD

J
E

E

J

DSS-d6

c)

D

D
HOD

(D)

J
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(E)

(J)

DSS-d6d)

10Deviation from preparation value (%)

Deviation from preparation value (%)(phenyl)Dphenyl

D E

J

J

E

D

0
-10
-20
-30
-40
-50
0

100
200
300
RF irradiation strength (Hz)

400

10
0
-10
6
4
2
0
-2
-4
-6

-20
-30
-40

0

100

200

300

400

-50
0

100
200
300
RF irradiation strength (Hz)400

Fig. 1. Changes in measured concentration values by 1H-qNMR with pre-SAT or dual pre-SAT.
1

H NMR spectra of D2O solutions obtained using (a) pre-SAT or (b) dual pre-SAT are shown. The maximum
range of RF irradiation attenuations for (c) pre-SAT or (d) dual pre-SAT was 112 dB to 40 dB. Error bars show
the doubled standard deviation obtained by three repeated measurements at the same attenuation.

ㅰ㎡ ᮏ◊✲ࡣJSPS⛉◊㈝JP22K14710ࡢຓᡂࢆཷࡅࡓࡶࡢ࡛ࡍࠋࡲࡓࠊ ᐃ࡟ࡣᅜ❧⎔ቃ◊✲ᡤᇶ┙ィ ᶵჾࡢNMR⿦⨨ࢆ฼⏝ࡋࡲࡋࡓࠋ
References [1] Mo and Raftery, J. Magn. Reson., 190(1), 1-6 (2008). [2] ᯇᮏ࡯࠿, 㛵⛯୰ኸศᯒᡤ

ሗ, (61), 31-44 (2021). [3] Akira et al., Chem. Pharm. Bull., 69(8), 721-726 (2021).

－ 149 －

P10Y ኚㄪࡋࡓ࣐࢖ࢡࣟἼࢆ⏝࠸ࡓືⓗ᰾೫ᴟຠ⋡ࡢྥୖ‫ۑ‬ᙇ௰Ⰻ ᯇᮌ㝧 ⸨ཎᩄ㐨


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1. ኱㜰኱Ꮫ࣭⺮ⓑ㉁◊✲ᡤ
2. ኱㜰኱Ꮫ㔞Ꮚ᝟ሗ࣭㔞Ꮚ⏕࿨◊✲ࢭࣥࢱ࣮

Improvement of dynamic nuclear polarization efficiency using modulated microwave‫ۑ‬Zhongliang Zhang1, Yoh Matsuki1,2, Toshimichi Fujiwara1,2
1

Institute for Protein Research, Osaka University

2

Center for Quantum Information and Quantum Biology, Osaka University
In magic-angle spinning dynamic nuclear polarization NMR (DNP-MAS-NMR), depending on the

microwave irradiation frequency, NMR signal is enhanced positively or negatively. Rapidly frequency
modulated microwave allows us to irradiate multiple frequencies. We developed methods to apply
frequency modulated microwave to obtain higher DNP-NMR signal enhancement and better spatial
selectivity, both being of crucial importance for intra-cellular applications. Our spin dynamics simulation
showed irradiation on two of the positive DNP enhancement peaks of Mn(II)-DOTA by turns produced ahigher NMR enhancement. And we developed a pulse sequence utilizing both the positive and negative
DNP enhancement peaks with frequency modulated microwave to suppress background NMR signals.
Simulation on spin diffusion and experiments showed the mechanism and effectiveness of our method.
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Fig. 1. Pulse sequence for backgroundsignal suppression

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the background suppression

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P11

☢ሙᤲᘬSWIFT࡟ࡼࡿ3ḟඖMRI‫⏣⃝ۑ‬Ọ㸪Ṋ⏣࿴⾜1ி㒔኱Ꮫ ኱Ꮫ㝔⌮Ꮫ◊✲⛉

3D field-swept SWIFT MRI‫ۑ‬Haruka Sawada1, Kazuyuki Takeda1
1

Division of Chemistry, Graduate School of Science, Kyoto University
A variant of SWIFT (SWeep Imaging with Fourier Transformation) MRI employing magnetic-fieldsweep instead of the conventional frequency sweep requires the actual profile of the swept magnetic field
for accurate data reconstruction and thereby artifact-free imaging.

SWIFT (SWeep Imaging with Fourier
Transform)1,2ἲࡣMRI᧜ീἲࡢ୍ࡘ࡛࠶ࡾࠊ㦁㡢ࡀᑠࡉࡃܶଶࡀ▷࠸⣔࡟ࡶ㐺⏝࡛ࡁࡿ࡜࠸࠺
≉ᚩࢆࡶࡘࠋSWIFT࡛ࡣഴᩳ☢ሙࡢᏑᅾୗ࡛
ᚓࡽࢀࡿrapid scan NMRಙྕࢆฎ⌮ࡋ࡚⏬ീࢆྲྀᚓࡍࡿࠋrapid scan࡟ࡣ࿘Ἴᩘᤲᘬࡀ⏝࠸ࡽࢀࡿࠋ୍᪉ࠊ☢ሙᤲᘬࢆ⏝࠸࡚SWIFTࢆᐇ⾜ࡍࢀࡤࠊ㉸㟁ᑟrfࢥ࢖ࣝࡸElectro-MechanoOptical (EMO) NMRࣔࢪ࣮ࣗࣝ࡞࡝ࡢ⊃ᖏᇦࡢ᳨ฟჾࢆ⏝࠸ࡓMRI᧜ീࡀᐇ⌧ࡍࡿ࡜ᮇᚅࡉ
ࢀ࡚࠸ࡿ3ࠋ

Fig. 1. A snapshot of home-made field-gradientࡇࢀࡲ࡛࡟ࠊ☢ሙᤲᘬᆺࡢSWIFTࢆ⏝࠸ࡓ(left) and field-sweep (right) coils.

MRIࡀሗ࿌ࡉࢀ࡚࠸ࡿࡀࠊ᧜ീࡣ2ḟඖ࡟࡜࡝ࡲࡾࠊࡲࡓ࢔࣮ࢸ࢕ࣇ࢓ࢡࢺ࡟ࡼࡿ⏬ീࡢࡦࡎࡳࡶ኱ࡁ࠿ࡗࡓ3ࠋࡇࡇ࡛ᡃࠎࡣࠊ☢ሙᤲᘬ

1H

SWIFT࡟ࡼࡿ3ḟඖMRI᧜ീ࡜ࠊ☢ሙᤲᘬ࡟㉳Samplingᅉࡍࡿ࢔࣮ࢸ࢕ࣇ࢓ࢡࢺࡢ㝖ཤ࡟ࡘ࠸࡚ሗ࿌
ࡍࡿࠋᮏ◊✲࡛ࡣࠊ┤ᚄ20 mmࡢࢥ࢖ࣝࢆ⏝࠸ࡓField

300 MHzᖏඹ᣺ᅇ㊰࡜࡜ࡶ࡟ࠊഴᩳ☢ሙࢥ࢖ࣝ࡜☢ሙᤲᘬࢥ࢖ࣝ(Fig. 1)ࢆ⮬సࡋࠊ7 Tࡢ㉸㟁ᑟ࣐ࢢࢿࢵࢺ࡜MRI௙ᵝ࡟ᨵ㐀ࡋࡓ
Opencore NMR4ศගィࢆ⏝࠸࡚Fig. 2࡟♧ࡍ☢

Gradient
Fig. 2. A pulse sequence for field-swept SWIFT.

ሙᤲᘬSWIFTࢩ࣮ࢣࣥࢫࢆᐇ⾜ࡋࠊ8.9 mmࡢ࢞ࣛࢫ⌫࡟‶ࡓࡋࡓCuSO4Ỉ⁐ᾮࡢ᧜ീᐇ㦂ࢆ⾜ࡗࡓࠋࡲࡓࠊ⏬ീࢆᵓᡂࡍࡿࡓࡵ࡟ᚲせMRI㸪SWIFT㸪☢ሙᤲᘬ‫࠿ࡿࡣࡔࢃࡉۑ‬㸪ࡓࡅࡔ࠿ࡎࡺࡁ

－ 152 －

࡞deconvolutionࠊࢹ࣮ࢱ⿵㛫ࠊ࠾ࡼࡧ3ḟඖ(a)ࣇ࣮࢚ࣜኚ᥮ࢆ⾜࠺ࡓࡵ࡟ࠊ࣮࢜ࣉࣥࢯ࣮
ࢫࢯࣇࢺ࢙࢘࢔Opencore NMR Process5ࢆᣑ

1H

ᙇࡋࡓࠋ
ᡃࠎࡣࠊ☢ሙᤲᘬࡢไᚚಙྕࡢᙧ≧࡜ࠊ

Fieldᐇ㝿࡟Ⓨ⏕ࡍࡿ☢ሙࡢ᫬㛫౫Ꮡᛶ࡟ࡣ┦㐪ࡀ࠶ࡾࠊ⏬ീ࡟኱ࡁ࡞࢔࣮ࢸ࢕ࣇ࢓ࢡࢺ(b)

ࡀⓎ⏕ࡍࡿせᅉ࡜࡞ࡗ࡚࠸ࡿࡇ࡜࡟Ẽ࡙࠸ࡓࠋࡑࡇ࡛ᡃࠎࡣࠊFig. 3(a)࡟♧ࡍࡼ࠺࡟ࠊ
ഴᩳ☢ሙࢆ࠿ࡅࡎ࡟☢ሙᤲᘬࡋ࡞ࡀࡽ 1H
ᐃࢆ⾜࠸ࠊᚓࡽࢀࡓ

0

1

2

3

4

5

4

5

Time / ms

FID(Fig. 3(b))࠿ࡽࠊᐇ㝿࡟Ⓨ⏕ࡋ࡚࠸ࡿᤲ

(c)ᘬ☢ሙࡢ᫬㛫౫Ꮡᛶࢆồࡵࡓ(Fig. 3(c))ࠋࡇࢀࢆ⏝࠸࡚rapid scanࢹ࣮ࢱࡢdeconvolutionฎ⌮ࢆ⾜࠸ࠊgridding6,7࡟ࡼࡿ⿵㛫ࠊ3ḟඖࣇ࣮࢚ࣜኚ᥮ࢆ⤒࡚ࠊFig. 4࡟♧ࡍࡦࡎࡳࡸ࢔
࣮ࢸ࢕ࣇ࢓ࢡࢺࡢ࡞࠸⏬ീࢆᚓࡿࡇ࡜ࡀ

Offset frequency/ kHzࢩࣥࢢࣝࣃࣝࢫ

20
0
-20

0

1

࡛ࡁࡓࠋ

2

3

Time / ms
Fig. 3. (a) A pulse sequence used to monitor the
profile of the swept field. (b) The in-phase (black)and the quadrature (gray) components of a 1H FID
in water with the field sweep applied duringacquisition. (c) The actual (solid line) and theprogrammed (broken line) profiles of the swept field.

(a)

(b)

(c)

(d)

(e)

Fig. 4. (a) An 8.9 mm spherical phantom filled with 0.2 M aqueous solution of CuSO4 (b-e) MR
images obtained with field-swept SWIFT.
References[1] D. Idiyatullin, C. Corum, J.-Y. Park, M. Garwood, J. Magn. Reson. 181 (2006) 342-349.
[2] D. Idiyatullin, C. Corum, M. Garwood, J. Magn. Reson. 251 (2015) 19-25.
[3] ᑠᯘὒኴ䠈➉⭜Ύ஀⌮䠈Ṋ⏣࿴⾜䠈➨58ᅇ NMRウㄽ఍ (2019) YP21䠊
[4] K. Takeda, J. Magn. Reson. 192 (2008) 218–229.
[5] https://opencorenmr.github.io/opencorenmr-docs/[6] Jackson JI, Meyer CH, Nishimura DG, Macovski A, IEEE Trans. Med. Imaging 10 (1991) 473–478.
[7] Pipe JG, Menon P, Magn. Reson. Med. 41 (1999) 179–186.

－ 153 －

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ྠ㍈ࢳ࣮ࣗࣈࢆ⏝࠸ࡓqNMR࡟࠾ࡅࡿᐃ⟶ࣟࢵࢺ⟶⌮ࡢ㔜せᛶ

1‫ۑ‬ᑠ಴❧ᕫ 㸪ⱝᒣṇ㝯

1៞᠕⩏ሿ኱Ꮫ࣭ඛ➃⏕࿨⛉Ꮫ◊✲ᡤ
2㸦බ㈈㸧ᗉෆᆅᇦ⏘ᴗ᣺⯆ࢭࣥࢱ࣮

Tube lot-control improves the accuracy of coaxial tube qNMR‫ۑ‬Tatsuki Ogura1,2, Masataka Wakayama1
1

Institute for Advanced Biosciences, Keio University

2

Shonai Regional Industry Promotion Center
Coaxial tube NMR enables to analyze without mixing two solutions and to reuse of the solution for otherexperiments. Since the effective volume ratio measurement is essential for coaxial tube qNMR, the tube lotcontrol must be improving the accuracy and repeatability. Here, we evaluated the effective volume ratio of
each tube lot in various diameters of inner tubes using different solutions. As result, using ĳ2.5 mm innertubes recorded high repeatability of analyses. The tube lot-control is also necessary for enhancing thequantification.
࠙ ᗎ ㄽ ࠚ ᐃ 㔞 NMR

Lot A Lot B Lot C㸦 qNMR㸧ࡣ ࢧ ࣥ ࣉ ࣝ୰ ࡢ 1 Hᩘ ࡀ ࣆ ࣮ ࢡ 㠃✚࡜ẚ౛㛵ಀ࡟࠶ࡿ

Quantified
reference(DSS)ࡇ࡜ࢆ฼⏝ࡋࡓศᯒ

Analyte(MA, Sar)ἲ࡛࠶ࡾࠊ㉁㔞ศᯒ

Shigemi coaxial tube
(SP401-405)

ィ㸦 MS㸧ࡸ ㉥ እ ศ ගFormula 1 (Peak area ratio)㔞ᶆ‽≀㉁࠿ࡽᵝࠎ࡞≀㉁ࡢᐃ㔞ゎᯒࡀ

qNMR
Formula 2 (Quantitation of analyte)‫ܫ‬஺ ‫ܪ‬ோ ࢂࡾࡵࡾ ‫ܯ‬ோ ܸோ ‫ܪ‬ோ‫ܯ‬஺ = ‫ܯ‬ோ × ××=××‫ܫ‬ோ ‫ܪ‬஺ ࢂ࡭ࡵ࡭ ‫ܯ‬஺ ܸ஺ ‫ܪ‬஺ἲ㸦 IR㸧࡜ ࡣ ␗ ࡞ ࡾ ࠊ⃰ᗘ᪤▱ࡢ୍ࡘࡢᐃ

Detector
coil

Comparison of
Evaluation of
Effective volume ratio affected to Quantitation

Effective
volume

M: Concentration, I: Peak area,
H: Number of 1H , V: volume,
R: Quantified reference, A: Analyte

Figure 1. The scheme of coaxial tube qNMR using individual lot-controlled
coaxial tube sets.

ྍ ⬟ ࡛ ࠶ ࡿ ࠋ qNMRἲࡢ୍ࡘ࡛࠶ࡿྠ㍈ࢳ࣮ࣗࣈἲࡣ2ᮏࡢ
࡜࠿ࡽࠊ㏻ᖖࡢNMR

Effective
volumeᐃ⟶ࢆ⤌ࡳྜࢃࡏ࡚౑⏝࡛ࡁࡿࡇᐃ࡜␗࡞ࡾࠊ2✀ࡢ␗࡞ࡿ⁐ᾮࢆΰྜࡍࡿࡇ࡜࡞ࡃ୍ࡘࡢNMRࢫ࣌ࢡࢺࣝ

ୖ࡛ศᯒྍ⬟࡛࠶ࡿࠋࡇࡢᐃ㔞ࡋࡓ⁐ᾮࡣᑐ㇟≀㉁௨እࡢ୙⣧≀ࡀΰධࡋ࡚࠸࡞࠸ࡓࡵࠊ௚

ᐃᶵჾ࡟࠾ࡅࡿᐃ㔞 ᐃࡢᶆ‽⁐ᾮࡸ⏕≀ᛂ⟅ヨ㦂࡞࡝࡬࡜ᐜ᫆࡟෌฼⏝࡛ࡁࡿࠋ
NMR࡟࠾࠸࡚ࠊ ᐃ࡟ᚲせ࡞⁐ᾮ㔞㸦᭷ຠᐜ✚㸧ࡣ᳨ฟࢥ࢖ࣝ࡟࠾ࡅࡿ᳨ฟྍ⬟㡿ᇦ࡜⪃࠼ࡽࢀࡿࡀࠊ⿦⨨ࡈ࡜࡟᳨ฟࢥ࢖ࣝࡢ኱ࡁࡉࡣ␗࡞ࡿࠋྠ㍈ࢳ࣮ࣗࣈqNMRἲࡣෆ⟶ࠊእ⟶ࡢ᭷ຠᐜ✚ẚࡀゎᯒ࡟ᚲせ࡜࡞ࡿࡀࠊࡑࡢ

ᐃἲ࡟ࡘ࠸࡚ࡣ☜❧ࡉࢀ࡚࠸࡞࠿ࡗࡓࠋᡃࠎࡣࡇࢀࡲ࡛ࠊ㔜㔞ᐃἲ࠾ࡼࡧqNMRἲࢆ⏝࠸ࡓ᭷ຠᐜ✚ẚ ᐃἲࡢᵓ⠏ࡋ࡚ࡁࡓ㸦Fig. 1㸧
㸦ISMAR-APNMR2021ࠊ
➨3ᅇᐃ㔞NMR◊✲఍㸧ࠋࡑࡢ㐣⛬࡟࠾࠸࡚ࠊෆ⟶࣭እ⟶ᐜ✚ẚࢆࣟࢵࢺࡈ࡜࡟⟶⌮ࡍࡿࡇ࡜࡛ᐃ
㔞⢭ᗘࡢྥୖࡢྍ⬟ᛶࡀ♧၀ࡉࢀࡓࠋᮏ◊✲࡛ࡣෆ⟶ᚄࡢ␗࡞ࡿྠ㍈ࢳ࣮ࣗࣈࡢྛࣟࢵࢺ࡟࠾ࡅ
ࡿ᭷ຠᐜ✚ẚࢆqNMRἲ࡟ࡼࡾ⟬ฟࡋࠊྠ㍈ࢳ࣮ࣗࣈෆ⟶ᚄ࠾ࡼࡧࣟࢵࢺ⟶⌮࡟㛵ࡋ࡚⪃ᐹࡋࡓࠋᐃ㔞NMR㸪ྠ㍈ࢳ࣮ࣗࣈ㸪ᐃ⟶ࣟࢵࢺ‫ࡁࡘࡓࡽࡄ࠾ۑ‬㸪ࢃ࠿ࡸࡲࡲࡉࡓ࠿

－ 154 －

࠙᪉ἲࠚqNMR⏝ࡢᶆ‽≀㉁࡜ࡋ࡚DSS-d6ࠊᑐ㇟≀㉁࡜ࡋ࡚Maleic acid 㸦MA㸧ࠊSarcosine 㸦Sar㸧ࢆࡑࢀࡒࢀ⏝ពࡋࠊศᯒ⏝ࢭ࣑࣑ࢡࣟኳ⛗࡛ࡑࢀࡒࢀ⛗㔞ࡋࡓࠋ⛗㔞ࡋࡓྛヨ⸆ࢆD2O⁐፹࡛⁐ゎࡋࠊ⤊⃰ᗘࡀ10mM㸦DSS㸧ࠊ50mM㸦MA, Sar㸧࡜࡞ࡿࡼ࠺࡟ㄪ〇ࡋࡓࠋㄪ〇ࡋࡓ⁐ᾮࡢ࠺ࡕࠊMA
࡜Sarࡣᕷ㈍ࡢ500mg/L DSSᶆ‽⁐ᾮ(2.233mM)࡜ࡢΰྜ⁐ᾮࢆqNMRゎᯒࡋࠊᐃ㔞್ࢆồࡵࡓࠋࡲ
ࡓ10mM DSS⁐ᾮࡣᐃ㔞ࡋࡓ50mM MA⁐ᾮ࡜ࡢΰྜᾮࢆㄪ〇ࡋࠊqNMR࡟ࡼࡿᐃ㔞್⟬ฟࢆ⾜ࡗࡓࠋ ᐃ⟶࡜ࡋ࡚ࢩࢤ࣑〇ࡢྠ㍈ࢳ࣮ࣗࣈ㸦ෆ⟶ୗ㒊እᚄ: ȭ1.7㹼3mm㸧ࢆྛ3ࢭࢵࢺ⏝࠸ࠊෆ⟶ࠊእ⟶ࡑࢀࡒࢀ࡟ࡘ࠸࡚ࣟࢵࢺ␒ྕࢆ⾲グࡋࡓࠋྛෆ⟶࡟ࡣᐃ㔞῭ࡳࡢ10mM DSS⁐ᾮࠊእ⟶࡟ࡣ
50mM MAࡲࡓࡣSar⁐ᾮࢆࡑࢀࡒࢀ඘ሸࡋࠊqNMRἲࢆ⏝࠸ࡓ᭷ຠᐜ✚ẚ ᐃ࡟⏝࠸ࡓࠋ
qNMR

ᐃ࡟ࡣJeol〇ࡢ600MHz NMRࢆ⏝࠸ࠊ13Cࢹ࢝ࢵࣉࣜࣥࢢ 1H-NMR ᐃࢆ⾜ࡗࡓࠋ ᐃ᮲௳࡜ࡋ࡚ࠊ⿦⨨ ᗘ25ႏࠊ⦆࿴᫬㛫60⛊ࠊ✚⟬ᅇᩘ32ᅇ࡛ ᐃࢆ⾜ࡗࡓࠋᚓࡽࢀࡓࢹ࣮ࢱࡣDeltaࢯࣇࢺ࢙࢘࢔㸦ver.5. 3. 1, Jeol〇㸧ࢆ⏝࠸࡚ゎᯒࡋࠊྛࣆ࣮ࢡࡢ㠃✚್ࢆྲྀᚓᚋࠊ᭷ຠᐜ✚ẚ ᐃࢆᐇ᪋ࡋࡓࠋ
OH

࠙⤖ᯝ࣭⪃ᐹࠚࣟࢵࢺ㛫ࡢ᭷ຠᐜ✚ẚࡢࣂࣛࡘࡁࢆ
CH(MA)

ホ౯ࡍࡿࡓࡵࠊྛྠ㍈ࢳ࣮ࣗࣈ࡟࠾ࡅࡿ᭷ຠᐜ✚ẚࢆ

OH O
OH

O

⟬ฟࡋࡓࠋࣟࢵࢺ㛫ࡢ᭷ຠᐜ✚ẚࡢኚືಀᩘ㸦CV㸧ࡣ

Maleic acid (MA)ȭ3mmෆ⟶ࡀ0.7%࡛᭱ࡶపࡃࠊෆ⟶ᚄࡀ⣽ࡃ࡞ࡿ࡟ᚑ

DSS-d6

࠸CVࡀቑ኱ࡋࡓ㸦Table 1㸧ࠋࡇࡢࡇ࡜࠿ࡽࠊྠ㍈ࢳࣗ

10 mM DSS/ 50 mM MA࣮ࣈࢆ⏝࠸ࡓqNMR࡛ࡣࣟࢵࢺࡈ࡜ࡢ᭷ຠᐜ✚ẚࢆỴCH3(Sar)ᐃࡍࡿᚲせࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡓࠋO

CH2(Sar)HO

MA࠾ࡼࡧSarࢆ⏝࠸࡚⟬ฟࡋࡓྛྠ㍈ࢳ࣮ࣗࣈࡢ
᭷ຠᐜ✚ẚࢆẚ㍑ࡋࠊ᭷ຠᐜ✚ẚ ᐃࡢ෌⌧ᛶࢆ☜ㄆࡋࡓ㸦Table 2㸧ࠋȭ2.5mmෆ⟶ࢆ⏝࠸ࡓሙྜࡢ᭷ຠᐜ
✚ẚࡢ೫ᕪࡣ2.2%௨ୗ࡜᭱ࡶᑠࡉࡃࠊࡑࡢ࡯࠿ࡢෆ⟶ᚄ࡛ࡣࣟࢵࢺ࡟ࡼࡗ࡚᭷ຠᐜ✚ẚࡀ2.5%௨ୖ␗࡞ࡗ

H
N

CH3
Sarcosine (Sar)

10 mM DSS/ 50 mM Sar
7.0

6.0

5.0

4.0

įH (ppm)

3.0

2.0

1.0

0

Figure 2. 1H-qNMR spectrum of DSS/MA
and DSS/Sar using ĳ2.5 mm coaxial tube.

࡚࠸ࡓ㸦Table 2. ⥙᥃ࡅ㸧ࠋྛ ᐃࡢࣆ࣮ࢡ㠃✚್࠿ࡽ ᐃᏳᐃᛶࢆホ౯ࡋࡓ⤖ᯝࠊȭ2.5mmෆ⟶౑⏝᫬ࡀ᭱ࡶ ᐃ㛫ࡢCVࡀᑠࡉ࠿ࡗࡓࠋ
௨ୖࡢ⤖ᯝ࠿ࡽࠊྠ㍈ࢳ࣮ࣗࣈࢆ⏝࠸ࡓqNMR࡟࠾࠸࡚ࠊ
ࣟࢵࢺ⟶⌮ࡉࢀࡓȭ2.5mmෆ⟶ࢆ⏝࠸ࡿࡇ࡜࡛ࠊᐃ㔞ᛶࡢ㧗࠸ゎᯒࡀྍ⬟࡟࡞ࡿ࡜⪃࠼ࡽࢀࡓࠋ
Table 1. Effective volume ratio of coaxial tubes (Inner tube: DSS, Outer tube: MA).
Inner tube
o.d. (mm)
1.7
2
2.5
3

Tube lot1
Mean ± SD
0.098 ± 0.001
0.165 ± 0.000
0.304 ± 0.001
0.710 ± 0.001

CV (%)
0.917
0.298
0.236
0.167

2
Mean ± SD
0.102 ± 0.001
0.160 ± 0.001
0.306 ± 0.001
0.701 ± 0.002

CV (%)
0.544
0.654
0.425
0.241

3
Mean ± SD
0.096 ± 0.001
0.159 ± 0.000
0.315 ± 0.001
0.699 ± 0.003

CV (%)
0.985
0.233
0.229
0.432

All
Mean ± SD
0.099 ± 0.003
0.161 ± 0.003
0.308 ± 0.005
0.703 ± 0.005*Effective volume ratio
CV (%)
2.744
1.711
1.553
0.745

(VR/VA) was calculatedusing changed formula 2
in Fig 1.

Table 2. Deviation of effective volume ratios calculated
from Sar and those from MA analyses.
Inner tube
o.d. (mm)
1.7
2
2.5
3

Combination ofmolecular structure
Sar (CH3) /MA (CH)Deviation of V R /V A of Sar/MA (%)
Lot 1
Lot 2
Lot 3
1.46
-6.09
2.19

Sar (CH2) /MA (CH)

1.84

-5.73

2.57

Sar (CH3) /MA (CH)

-2.39

1.76

2.69

Sar (CH2) /MA (CH)

-1.98

2.09

3.02

Sar (CH3) /MA (CH)

1.91

0.93

0.79

Sar (CH2) /MA (CH)

2.20

1.32

1.08

Sar (CH3) /MA (CH)

1.23

3.26

2.69

Sar (CH2) /MA (CH)

1.61

3.63

2.82

*The deviation was calculated from following formula.
ܸAverage ோ of Sarܸ஺Deviation (%) = 100 െܸோAverage of Marܸ஺－ 155 －

P13

㧗☢ሙB1୙ᆒ୍ศᕸ࡛ࡢࣄࢺ⬻1H MRS௦௦ㅰ≀ᐃ㔞໬ἲࡢ㛤ⓎɧΏ㑓ⱥᏹ1㸪㧗ᒇᒎᏹ1㸪ᩪ⸨┤ᶞ11ᅜ❧◊✲㛤Ⓨἲே ᅜ❧⎔ቃ◊✲ᡤ ⎔ቃࣜࢫࢡ࣭೺ᗣ㡿ᇦ

Development of quantitative measurement methods of metabolites on 1H MRS in humanbrain under inhomogeneous B1 at high field
Hidehiro Watanabe1, Nobuhiro Takaya1, Naoki Saito1
1

Health and Environmental Risk Division, National Institute for Environmental Studies

The method for measurement of metabolite concentrations in 1H MRS in a human brain at high B0 field was
proposed. A water phantom as a reference and a human brain area measured separately. The ratio of thereception sensitivities between uniform areas in the phantom and in the human brain can be computed frommeasured B1+s. The ratio between the VOI and the uniform area in the human brain can be computed by ourpreviously reported ratio map method. Then, metabolite concentrations in the VOI can be calculated. Our
method was demonstrated in the phantom experiments using metabolite mixtures.
㸯㸬ࡣࡌࡵ࡟㠀౵く࡟ᒁᡤ㡿ᇦ࠿ࡽࡢ 1H ࢫ࣌ࢡࢺࣝ ᐃࡀฟ᮶ࡿ 1H MRS ࡛ࡣࠊ㧗☢ሙ MRI ࢆ฼⏝ࡍࡿࡇ࡜࡛㧗ឤᗘࠊࣆ࣮ࢡࡢ㧗ศゎࡢ≉ᚩࢆ᭷ࡍࡿ㉁ࡢⰋ࠸ࢫ࣌ࢡࢺࣝࡢྲྀᚓࡀᮇᚅฟ᮶ࡿࠋࡇࡢࡓࡵࠊ
ศᯒ⏝ NMR ࢫ࣌ࢡࢺ࣓࣮ࣟࢱ࣮࡜ྠᵝࠊ㧗☢ሙࡣᐃ㔞 ᐃ࡟᭷฼࡛࠶ࡿࠋࡋ࠿ࡋࠊ ᐃᑐ㇟ࡀඹ㬆࿘Ἴᩘࡢ㟁☢ἼἼ㛗࡜ྠ⛬ᗘ࡜࡞ࡿ㧗☢ሙ MRI ࡛ࡣࠊRF ࢥ࢖ࣝ࡟㉳ᅉࡍࡿ B1 ศᕸ୙ᆒ୍
ᛶࡔࡅ࡛ࡣ࡞ࡃࠊ ᐃᑐ㇟ࡀㄏ㟁య࡛࠶ࡿࡇ࡜࡟㉳ᅉࡍࡿࠊࡘࡲࡾ⿕᳨య⏤᮶ࡢ B1 ୙ᆒ୍ศᕸ
ࡀ⏕ࡎࡿࠋࡇࡢࡓࡵࠊእ㒊ᶆ‽ヨᩱࢆタ⨨ࡋ࡚ࠊࡇࡢ᥮⟬࠿ࡽ⤯ᑐᐃ㔞໬ࠊࡍ࡞ࢃࡕ⃰ᗘᐃ㔞໬ࢆ⾜࠺ࡓࡵ࡟ࡣࠊࡇࡢ B1 ୙ᆒ୍ศᕸࢆ⪃៖ࡍࡿᚲせࡀ࠶ࡿࠋࡇࢀ࡟ᑐࡋ࡚ࠊ㏆ᖺࠊᵝࠎ࡞ B1 ᙉᗘศᕸ ᐃἲࡀᥦ᱌ࠊ
㛤Ⓨࡉࢀ࡚࠸ࡿࠋࡇࢀࢆ฼⏝ࡋ࡚ B1 ศᕸࢆ ᐃࡋࠊእ㒊ᶆ‽ヨᩱࡢ఩⨨࡜ᒁᡤ㡿ᇦࡢᐃ఩⨨࡜ࡢឤᗘᕪࢆ⪃៖ࡍࢀࡤࠊ⃰ᗘ᥮⟬ࡀฟ᮶ࡑ࠺࡛࠶ࡿࠋ୍᪉ࠊMRI ࡢࡳ࡞ࡽࡎ
NMR ࡶྵࡵࡓ☢Ẽඹ㬆 ᐃ࡟㛵ࡋ࡚ࠊ㏆ᖺࠊ㏦ಙ B1 ࡜ཷಙ
B1 ࡀ␗࡞ࡾࠊࡑࢀࡒࢀ B1+, B1-࡜⾲ࡏࡿࡇ࡜ࡀศ࠿ࡗ࡚ࡁ࡚
࠸ࡿ 1ࠋᡃࠎࡢ 4.7T MRI ࡛ࡢᐇ㦂࠿ࡽࡶࠊ⏕⌮㣗ሷỈࢆᑒධࡋࡓ⌫ࣇ࢓ࣥࢺ࣒ࡢ㏦ಙ B1 ศᕸ࡜ཷಙ B1 ศᕸࡀ┦␗ࡍࡿ

Fig. 1 Transmission field (left) andreception field (right) of a sphere
phantom filled with saline measured at
4.7T.

ᵝᏊࡀ ᐃࡉࢀ࡚࠸ࡿ㸦Fig. 1㸧
ࠋୖ㏙ࡢ B1 ᙉᗘศᕸ ᐃࡣࠊ㏦ಙ B1 ศᕸࢆ ᐃࡍࡿ᪉ἲ࡛࠶
ࡿࠋ୍᪉ࠊཷಙ B1 ศᕸࠊࡍ࡞ࢃࡕཷಙឤᗘࡣࠊNMR ಙྕ࡟஌ࡌ࡚ ᐃࡉࢀࡿࡓࡵࠊFig.1 ࡟♧ࡍᵝ࡞ᆒ୍ヨᩱ௨እ࡛ࡣ ᐃࡍࡿࡇ࡜ࡀฟ᮶࡞࠸ࠋࡇࡢࡓࡵࠊឤᗘᕪࢆồࡵࡿࡇ࡜ࡀฟ᮶ࡎࠊ㧗☢ሙ MRI ࡛ࡣእ㒊ᶆ‽ヨᩱࢆ⏝࠸ࡿ᪉ἲࢆ฼⏝ฟ᮶࡞࠸ࠋ
ࡑࡇ࡛ࠊࣄࢺ⬻࡛ࡣෆ㒊Ỉᶆ‽ἲ࡜࠸࠺᪉ἲࢆ⏝࠸࡚⤯ᑐᐃ㔞໬ࢆ⾜ࡗ࡚࠸ࡿࠋࡇࡢ᪉ἲ࡛
ࡣࠊࣄࢺ⬻ෆ࡛౛࠼ࡤ๓㢌ⴥ㡿ᇦ࡞࡝ࡢ㝈ᐃࡉࢀࡓ㛵ᚰ㡿ᇦ㸦VOI㸧࠿ࡽྲྀᚓࡉࢀࡓỈࢫ࣌ࢡࢺࣄࢺ⬻1Hࢫ࣌ࢡࢺࣝ㸪㧗☢ሙ㸪⤯ᑐᐃ㔞໬ɧࢃࡓ࡞࡭ࡦ࡛ࡦࢁ㸪ࡓ࠿ࡸࡢࡪࡦࢁ㸪ࡉ࠸࡜࠺࡞࠾ࡁ

－ 156 －

ࣝ㠃✚࡜ࠊVOI ෆࡢྵỈ㔞࡜ࡢ㛵ಀࢆ⏝࠸ࡿࠋྵỈ㔞ࡣࠊVOI ෆࡢ⅊ⓑ㉁ࠊⓑ㉁ࠊ⬻⬨㧊ᾮࡢ㡿ᇦࢆศ⏬ࡋ࡚ࠊࡑࢀࡒࢀࡢྵỈ㔞᪤ሗ್࠿ࡽ⟬ฟࡍࡿࠋࡋ࠿ࡋࠊ⑌ᝈ࡞࡝ࡢྵỈ㔞ኚ໬ࡀ᝿ᐃࡉ
ࢀࡿሙྜ࡟฼⏝ࡀฟ᮶࡞࠸ࠊVOI ෆࡢཷಙឤᗘศᕸࡢ⪃៖ࡀᚲせ࡞࡝ࡢၥ㢟ࡀ࠶ࡗࡓࠋ௒ᅇࠊࡇ
ࡢၥ㢟ࢆゎỴࡍࡿࡓࡵ࡟ࠊᡃࠎࡀࡇࢀࡲ࡛࡟ሗ࿌ࡋ࡚ࡁࡓ⏬ീᆒ୍㡿ᇦ࡛ࡢ㏦ಙ B1 ࡜ཷಙឤᗘ
ࡢྠ➼ᛶࢆ฼⏝ࡋࡓࠊࣄࢺ⬻ෆ௦ㅰ≀ࢫ࣌ࢡࢺࣝࡢ⤯ᑐᐃ㔞໬ἲࢆᥦ᱌ࠊ㛤Ⓨࡋࠊࣇ࢓ࣥࢺ࣒ᐇ
㦂ࢆ⾜ࡗࡓࡢ࡛ሗ࿌ࡍࡿࠋ
㸰㸬᪉ἲᥦ᱌ἲ࡛ࡣࠊ⃰ᗘᇶ‽ࣇ࢓ࣥࢺ࣒㸦Ỉ㸦55.55 M㸧ࢆᑒධ㸧࡜ࣄࢺ⬻࡛ࡑࢀࡒࢀ ᐃࢆ⾜࠸ࠊB1+ẚࢆ⟬ฟࡍࡿࠋࡇࢀࡲ࡛ࡢᡃࠎࡢሗ࿌࠿ࡽ㧗☢ሙ࡛ࡶᆒ୍㡿ᇦ࡛B1+࡜B1-ࡀྠ➼࡛࠶ࡾࠊࡑࢀࡒ
ࢀࡢᆒ୍㡿ᇦ࡛ࡢB1+ẚࡀB1-ẚ㸦ཷಙឤᗘẚ㸧࡟୍⮴ࡍࡿ㸦Fig. 2㸧ࠋࣄࢺ⬻࡛ࡢᆒ୍㡿ᇦ࡜VOI
㡿ᇦ࡜ࡢཷಙឤᗘẚࡣࠊᡃࠎࡀࡇࢀࡲ࡛࡟㛤Ⓨࡋࡓẚ⋡࣐ࢵࣉἲ 2ࢆ⏝࠸࡚⟬ฟࡍࡿࠋࡇࢀࡽࡢ
㛵ಀ࠿ࡽࠊᇶ‽ࣇ࢓ࣥࢺ࣒ࡢᆒ୍㡿ᇦ࡜ࣄࢺ⬻ෆVOI࡛ࡢཷಙឤᗘẚࡀ⟬ฟฟ᮶ࡿࠋࡇࡢ
᥮⟬⤖ᯝ࡜ࠊᇶ‽ࣇ࢓ࣥࢺ࣒ࡢᆒ୍㡿ᇦ࡛ᐃࡋࡓỈࢫ࣌ࢡࢺࣝ㠃✚࠿ࡽࠊࣄࢺ⬻VOI࡛Ỉ㸦⃰ᗘ55.55 M㸧ࢆ ᐃࡋࡓሙྜࡢࢫ࣌ࢡ
ࢺࣝ㠃✚ࡀ⟬ฟฟ᮶ࡿࠋᚑࡗ࡚ࠊ௦ㅰ≀ࢫ࣌ࢡࢺࣝ㠃✚࠿ࡽ⃰ᗘᐃ㔞໬ࡀྍ⬟࡜࡞ࡿࠋ

Fig. 2 Proposed quantitation method of metabolites
in human brain 1H MRS.

ᥦ᱌ἲࢆᐇドࡍࡿࡓࡵࠊࣄࢺ඲㌟⏝4.7T MRI㸦Agilent〇㸧ࢆ⏝࠸࡚ࣇ࢓ࣥࢺ࣒ᐇ㦂ࢆ⾜ࡗࡓࠋRFࢥ࢖ࣝ࡟ࡣࠊ㏦ཷಙව⏝TEMయ✚ࢥ࢖ࣝࢆ⏝࠸ࡓࠋᑐ㇟ࣇ࢓ࣥࢺ࣒࡜ࡋ࡚10 mMࡢNAAࠊCrࡢΰྜ⁐ᾮࢆᑒධࡋࡓᑠࣇ࢓ࣥࢺ࣒ࢆධࢀࡓ኱෇⟄ࣇ࢓ࣥࢺ࣒ࠊᇶ‽ࣇ࢓ࣥࢺ࣒࡜ࡋ࡚⏕⌮㣗ሷỈࢆᑒධࡋࡓ⌫ࣇ࢓ࣥࢺ࣒ࢆ⏝࠸ࡓࠋB1+ ᐃ࡟ࡣ఩┦ἲ࡛ࡢ࢖࣓࣮ࢪࣥࢢࠊB1- ᐃ࡟ࡣ᩿⇕ࣃࣝࢫ
SE࢖࣓࣮ࢪࣥࢢἲࠊࢫ࣌ࢡࢺࣝ

ᐃ࡟ࡣ8mlࡢVOI࠿ࡽSTEAMἲࢆ⏝࠸ࡓࠋᇶ‽ࣇ࢓ࣥࢺ࣒ࡢᆒ

୍㡿ᇦ࡛ࡢỈࢫ࣌ࢡࢺࣝࠊᑐ㇟ࣇ࢓ࣥࢺ࣒ࡢVOI࡛ࡢ௦ㅰ≀ࢫ࣌ࢡࢺࣝࢆྲྀᚓࡋࠊᥦ᱌ἲࢆ⏝࠸࡚௦ㅰ≀⃰ᗘࢆ⟬ฟࡋࡓࠋ㸱㸬⤖ᯝᇶ‽ࣇ࢓ࣥࢺ࣒࡜ᑐ㇟ࣇ࢓ࣥࢺ࣒ࡢᆒ୍㡿ᇦ࡛ࡢ B1+ࡣࠊࡑࢀࡒࢀࠊ0.218 KHzࠊ0.213 KHz ࡜ ᐃࡉࢀࡓࠋᑐ㇟ࣇ࢓ࣥࢺ࣒ෆࡢ B1-ẚ㍑࡛ࡣࠊᆒ୍㡿ᇦ࡜ VOI 㡿ᇦ࡜ࡢẚ⋡ࡀ 0.649 ࡜࡞ࡗࡓࠋᇶ‽ࣇ࢓ࣥࢺ࣒ࡢᆒ୍㡿ᇦ࡛ࡢỈࢫ࣌ࢡࢺࣝ㠃✚ࡀ 79.4 ࡛࠶ࡾࠊࡇࡢ⤖ᯝࠊᑐ㇟ࣇ࢓ࣥࢺ࣒ࡢ VOI ࡛ࠊ
55.55 M ࡢ⃰ᗘヨᩱ࡟ᑐࡋ࡚ࠊࢫ࣌ࢡࢺࣝ㠃✚ 0.213/0.218*0.649 = 50.3 ࡢࢫ࣌ࢡࢺࣝࡀ ᐃࡉࢀࡿ᥮⟬࡜࡞ࡗࡓࠋࡇࡢ㛵ಀࢆ฼⏝ࡋ࡚ࠊྲྀᚓࡉࢀࡓ STEAM ࢫ࣌ࢡࢺࣝ࠿ࡽ NAAࠊCr ࡢ⃰ᗘࢆồࡵࡓ⤖ᯝࠊࡑࢀࡒࢀ 10.7 mMࠊ11.1 mM ࡜⟬ฟࡉࢀࠊヨᩱ⃰ᗘ࡟㏆࠸್ࡀᚓࡽࢀࡓࠋ
㸲㸬ࡲ࡜ࡵᥦ᱌ࡍࡿ᪉ἲࡣࠊ㧗☢ሙ࡛ࡢ 1H MRS ᐃ㔞໬࡟᭷⏝࡛࠶ࡿࠋẚ⋡࣐ࢵࣉἲࢆ⏝࠸࡚ཷಙឤᗘẚࢆ⟬ฟࡍࡿࡇ࡜࡛ࣄࢺ⬻ 1H MRS ࡟㐺⏝ྍ⬟࡛࠶ࡾࠊ⤯ᑐᐃ㔞໬ࡀᮇᚅฟ᮶ࡿࠋ
References(1) Hoult DI., The principle of reciprocity in signal strength calculations – a mathematical guide. Concepts
Magn. Reson. 2000;12:173-187.
(2) Watanabe H., Takaya N., Mitsumori F. Non-uniformity correction of human brain at high field by RF
field mapping of B1+ and B1-. J. Magn. Reson. 2011;212(2):426-430－ 157 －

P14Y

CGGࣜࣆ࣮ࢺ⤖ྜ⸆๣ࢼࣇࢳࣜࢪࣥࢲ࢖࣐࣮࡟ࡼࡿDNAㄆ㆑ᶵᵓࡢNMRゎᯒ
‫ۑ‬Ḉᯘಟᖹ1, 2, ྂᯈᜤᏊ1, ᒣ⏣๛ྐ2, ⸨ཎᩄ㐨1, ୰㇂࿴ᙪ2, ඣᔱ㛗ḟ㑻1,3
1 ኱㜰኱Ꮫ⺮ⓑ㉁◊✲ᡤ,

2 ኱㜰኱Ꮫ⏘ᴗ⛉Ꮫ◊✲ᡤ,

3 ᶓ὾ᅜ❧኱Ꮫ኱Ꮫ㝔ᕤᏛ◊✲㝔

DNA recognition mechanism of naphthyridine dimer, a CGG repeat-binding drug,
analyzed by NMR‫ۑ‬Shuhei Sakurabayashi1, 2, Kyoko Furuita1, Takeshi Yamada2, Toshimichi Fujiwara1, Kazuhiko Nakatani1,
Chojiro Kojima1, 3
1 Institute for Protein Research, Osaka University,

2 SANKEN, Osaka University,

3 Graduate School of Engineering Science, Yokohama National University
More than 40 neurodegenerative disorders are caused by expansions of simple sequence repeats in thehuman genome. Fragile X syndrome is a repeat expansion disease caused by the aberrant CGG repeat
expansions in an FMR1 gene. Naphthyridine dimer is a synthetic small molecule binding to d(CGG/CGG)
triad found in the hairpin structure in CGG repeats. In this study, the binding of ND to a double-stranded
DNA (dsDNA) containing a d(CGG) triad (GG1) was investigated by NMR spectroscopy. NMR titration
experiments indicated that there are two different binding modes for the GG1-ND complex; the most stablestructure (GG1:ND = 1:2 complex) and the transient structure (GG1:ND = 1:1 complex). Based on the
structure and thermal stability of each complex, the DNA recognition mechanism of ND was discussed.
Keyword: DNA, ࣑ࢫ࣐ࢵࢳሷᇶᑐࠊపศᏊ

ࠚ
࠙ᗎㄽࠚ
䝠䝖䝀䝜䝮୰䛾 CXG 㓄ิ䛾␗ᖖఙ㛗䛻䜘䛳䛶⏕䛨䜛⚄⤒ኚᛶ⑌ᝈ䛿䝸䝢䞊䝖⑓䛸࿧䜀䜜䚸䛣䜜䜎䛷䛻 40 ✀㢮௨ୖ䛜▱䜙䜜䛶䛔䜛䚹䝸䝢䞊䝖⑓䛾
1 䛴䛷䛒䜛⬤ᙅ X ⑕ೃ⩌䛿䚸FMR1
㑇ఏᏊୖ䛾 CGG 䝸䝢䞊䝖䛾␗ᖖఙ㛗䛜ཎᅉ䛸䛥䜜䛶䛔䜛䚹䝸䝢䞊䝖⑓䛻ᑐ䛩䜛἞⒪ᡓ␎䛸䛧䛶䚸᭱㏆䝸䝢䞊䝖
DNA ୰䛾䝦䜰䝢䞁ᵓ㐀䜢Ᏻᐃ໬䛥䛫䜛పศᏊ䛜䝸䝢䞊䝖㛗䜢▷⦰䛩䜛䛣䛸䛜᫂䜙䛛䛻䛺䛳䛶䛚䜚䚸DNA ㄆ㆑ศᏊ䛻䜘䜛䝸䝢䞊䝖⑓䛾᰿἞἞⒪䛜ᮇᚅ䛥䜜䛶䛔䜛 1䚹ྜᡂపศᏊ䝘Fig.1 (A) Chemical structure of naphthyridine dimer (ND). (B)DNA sequence of GG1. The d(CGG/CGG) motif is highlighted inboldface. (C) ITC profiles of GG1 and ND.

䝣䝏䝸䝆䞁䝎䜲䝬䞊䠄ND, Fig.1A䠅䛿 CGG 䝸䝢䞊䝖䛜ᙧᡂ䛩䜛 d(CGG/CGG)䝰䝏䞊䝣䛻⤖ྜ䛩䜛䛣䛸䛜▱䜙䜜䛶䛚䜚 2䚸἞⒪⸆䜔デ᩿䛾䛯䜑䛾ศᏊ䝥䝻䞊䝤䛸䛧䛶䛾ᛂ⏝䛜ᮇᚅ䛥䜜䜛䚹
DNA䚸䝭䝇䝬䝑䝏ሷᇶᑐ䚸పศᏊ䚽䛥䛟䜙䜀䜔䛧 䛧䜕䛖䜈䛔䚸 䜅䜛䛔䛯 䛝䜗䛖䛣䚸 䜔䜎䛰 䛯䛡䛧䚸䜅䛨䜟䜙 䛸䛧䜏䛱䚸䛺䛛䛯䛻 䛛䛪䜂䛣䚸䛣䛨䜎 䛱䜗䛖䛨䜝䛖－ 158 －

ND 䛿 1,8-naphthyridine䠄NP䠅㒊఩䛜䜾䜰䝙䞁䛸┦⿵ⓗ䛺Ỉ⣲⤖ྜ䜢ᙧᡂ䛧䚸䝽䝖䝋䞁-䜽䝸䝑䜽ᵝ䛾ሷᇶᑐ䜢ᙧᡂ䛩䜛䛣䛸䛷 DNA 䜢㓄ิ㑅ᢥⓗ䛻ㄆ㆑䛩䜛䚹䛣䜜䜎䛷䛻䚸➼⁲ᐃᆺ䜹䝻䝸䝯䝖䝸䞊䠄ITC䠅ᐃ䛻䜘䛳䛶 1 䛴䛾 d(CGG/CGG)䝰䝏䞊䝣䛻ᑐ䛧䛶 2 䛴䛾 ND ศᏊ䛜⤖ྜ䛩䜛䛣䛸䛜♧၀䛥䜜䛶䛔䜛䛜䠄Fig.1C䠅䚸
ヲ⣽䛺ศᏊㄆ㆑䛾䝯䜹䝙䝈䝮䛿୙᫂䛷䛒䜛䚹ᮏ◊✲䛷䛿䚸CGG 䝦䜰䝢䞁ᵓ㐀୰䛻ぢ䜙䜜䜛 d(CGG/CGG)㓄ิ䜢ྵ䜐஧㔜㙐 DNA䠄GG1, Fig1B䠅
䠅䛸 ND 䛾」ྜయ䜢 NMR 䛻䜘䛳䛶ゎᯒ䛧䛯䚹⁲ᐃᐇ㦂䜘䜚䚸ND 䛿d(CGG/CGG)㓄ิ䛻ᑐ䛧䛶䚸2 ㏻䜚䛾⤖ྜᵝᘧ䜢䛸䜚䚸䛭䜜䛮䜜䛜᭱Ᏻᐃᵓ㐀䠄GG1:ND = 1:2䚸௨㝆 1:2」ྜయ䠅䛸㐣Ώⓗᵓ㐀䠄dsDNA:ND = 1:1䚸௨㝆 1:1 」ྜయ䠅䛷䛒䜛䛣䛸䛜ศ䛛䛳䛯䚹䛭䜜䛮䜜䛾」ྜయ䛾❧యᵓ㐀䛻ຍ䛘䚸⇕Ᏻᐃᛶ䜔໬Ꮫ஺᥮䛾ゎᯒ䜢⾜䛔䚸పศᏊ ND 䛻䜘䜛 DNA 㓄ิ䛾ㄆ㆑䝯䜹䝙䝈䝮䛻㛵䛩䜛⪃ᐹ䜢⾜䛳䛯䚹
࠙᪉ἲࠚ
NMR

ᐃ䛿඲䛶5%D2O䜢ྵ䜐pH 6.8䛾䝸䞁㓟䝘䝖䝸䜴䝮⦆⾪ᾮ୰䛷⾜䛳䛯䚹⁐፹ᾘཤ䛻䛿1-1 echo䚸

excitation sculpting䚸 䜎䛯䛿3-9-19䝟䝹䝇䜢⏝䛔䛯䚹⁲ᐃᐇ㦂䛷䛿䚸0.1 mM䛾GG1⁐ᾮ䛻ᑐ䛧䛶ND䜢1➼㔞䛪䛴⁲ୗ䛧䚸1D 1H 䝇䝨䜽䝖䝹䛾䜲䝭䝜䝥䝻䝖䞁㡿ᇦ䠄10-15 ppm䠅䜢䝰䝙䝍䞊䛧䛯䚹᭱Ᏻᐃᵓ㐀䠄1:2」
ྜయ䠅䛾❧యᵓ㐀ゎᯒ䛻䛿䚸2➼㔞䛾ND䜢ΰྜ䛧䛯2 mM䛾GG1⁐ᾮ䜢⏝䛔䛯䚹1H-1H NOESY䠄ΰྜ᫬㛫䛿30䛚䜘䜃200 msec䠅, TOCSY䚸 DQF-COSY䚸1H-31P HSQC䚸 1H-15N HSQC䠄15Nᶆ㆑䛧䛯ND䜢౑⏝䠅䛚䜘䜃natural abundance 1H-13C HSQC䝇䝨䜽䝖䝹䜢ᐃ䛧䚸NMRFAM-Sparky䜢⏝䛔䛶䝇䝨䜽䝖䝹䛾ᖐᒓ䜢⾜䛳䛯䚹NOESY䝇䝨䜽䝖䝹䠄ΰྜ᫬㛫䛿200 msec䠅䜢ᇶ䛻ィ⟬䝥䝻䜾䝷䝮MARDIGRAS䜢⏝䛔䛯䚹ṧవ཮ᴟᏊ┦஫స⏝䠄RDC䠅䛿䚸㓄ྥ๣䛸䛧䛶Pf1 phage䜢ῧຍ䛧䚸ⰾ㤶᪘䛾13C-1H䜹䝑䝥䝸䞁䜾䛾ศ⿣ᖜ䛾ᕪ␗䜢ồ䜑䜛䛣䛸䛻䜘䛳䛶್䜢ᚓ䛯䚹ィ⟬䝥䝻䜾䝷䝮CNS version 1.3䜢⏝䛔䛶䚸RDC䜢ྵ䜎䛺䛔ᣊ᮰᮲௳䛾䜒䛸䝅䝭䝳䝺䞊䝔䝑䝗䜰䝙䞊䝸䞁䜾䜢⾜䛔䚸100ᵓ㐀ィ⟬䛧䛯䛖䛱䛾NOE䛚䜘䜃஧㠃ゅ䛾㐪཯䛜䛺䛔ୖ఩30ᵓ㐀䛻ᑐ䛧䛶RDC䛾ᣊ᮰᮲௳䜢ຍ䛘䛶ィ⟬䜢⾜䛳䛯䚹ィ⟬䛻⏝䛔䛯ヲ⣽䛺ᣊ᮰᮲௳䛿table 1䛻䜎䛸䜑䛯䚹㐣Ώⓗᵓ㐀䠄1:1」ྜయ䠅䛾ゎᯒ䛿䚸1➼㔞䛾ND䜢ΰྜ䛧䛯2.7 mM䛾GG1⁐ᾮ䜢⏝䛔䛶䚸᭱Ᏻᐃᵓ㐀䛾ሙྜ䛸ྠᵝ䛻ྛ✀2ḟඖNMRᐃ䜢⾜䛔䚸ᖐᒓ䜢⾜䛳䛯䚹NMR䝇䝨䜽䝖䝹䜢ᇶ䛻䚸ศᏊ䝰䝕䝸䞁䜾䝟䝑䜿䞊䝆MacroModel䠄Schrödinger䠅䜢⏝䛔䛶䝰䝕䝸䞁䜾䜢⾜䛳䛯䚹࠙⤖ᯝࠚࠚ䐟 NMR ⁲ᐃᐇ㦂
GG1࡟NDࢆ⁲ୗࡋࠊ࢖࣑ࣀࣉ

GG1 : ND

T2/10
T15
T19 T20
T14˔

1 : 2.0

1'

G17/6
G18 G7˔

NP4 NP1

1'˓˓

NP2 NP3

ࣟࢺࣥ㡿ᇦ㸦10~14 ppm㸧ࡢ1D 1Hࢫ࣌ࢡࢺࣝࢆほ ࡍࡿࡇ࡜࡛」ྜయᙧᡂࢆ㏣㊧ࡋࡓ㸦Fig. 2㸧ࠋ
NDࢆGG1࡟ᑐࡋ࡚2➼㔞⁲ୗࡋ
ࡓᆅⅬ࡛ࢩࢢࢼࣝኚ໬ࡀ㣬࿴ࡋࡓࡇ࡜࠿ࡽࠊࡇࡢᆅⅬ࡛ࡣ1:2」
ྜయࡢࡳࡀᙧᡂࡉࢀ࡚࠸ࡿࡇ࡜
ࡀศ࠿ࡗࡓࠋࡲࡓNDࢆ1➼㔞⁲ୗࡋࡓᆅⅬ࡛ࡣࠊ1:2」ྜయ࡜ࡣ
ู࡟1:1㸦= GG1:ND㸧」ྜయࡀᙧ

1 : 1.0

1:0(DNA only)

T2/14
T15/20 T10
T19

˔

G18
8 G7
˔

Fig.2 1D 1H spectra of GG1 in the presence of ND with various
GG1-ND ratios at 283 K. The molar ratio of GG1 and ND wasshown in the left (GG1:ND). NPn (n=1~4) indicate the amide
protons of ND.

ᡂࡉࢀ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋNDࡢῧຍ࡟క࠸10~12.5ppm࡟᪂ࡓ࡞ࣆ࣮ࢡࡀฟ⌧ࡋࠊNP࡜ࢢ࢔ࢽࣥ㛫࡛ࡢỈ⣲⤖ྜࡢᙧᡂࡀ♧၀ࡉࢀࡓࠋࣇ࣮ࣜࡢDNAࠊ1:1」ྜయࠊ1:2」ྜయࡣNMRࡢࢱ࢖࣒ࢫ
ࢣ࣮ࣝ࡟࠾ࡅࡿslow exchangeࡢࣃࢱ࣮ࣥࢆ♧ࡋࡓࠋ－ 159 －

ղ 」ྜయࡢ⇕Ᏻᐃᛶ

Free GG1
FRPSOH[
FRPSOH[
T19T14 T15
40 Υ T20⁲ᐃᐇ㦂ࡼࡾࠊND ࢆ 1 ➼㔞⁲ୗࡋࡓ≧ែ࡛ࡣࠊࣇ࣮ࣜࡢ DNA ࡜ 1:1 」ྜయࠊ1:2 」ྜ

G17/6
G18 G7NP4NP1 NP2

NP3

యࡢ 3 ✀ࡢ໬Ꮫ✀ࡀᏑᅾࡍࡿࡇ࡜ࡀศ࠿ࡗ
ࡓࠋࡇࡢ᮲௳ୗ࡛ࠊᵝࠎ࡞

ᗘ࡛

ᐃࢆ⾜࠺

30 Υ

ࡇ࡜࡛ࠊࡑࢀࡒࢀࡢ⇕Ᏻᐃᛶࢆㄪ࡭ࡓࠋࡑࡢ
⤖ᯝࠊ30 ࠿ࡽ 40 Υࡢ㛫࡛ࠊࣇ࣮ࣜࡢ DNA ࡜

20 Υ

1:1 」ྜయࡣ஧㔜㙐ࡀゎ㞳ࡋ࡚࠸ࡿࡢ࡟ᑐࡋࠊ

10 Υ

1:2 」ྜయࡣ 40 ΥᆅⅬ࡛ࡶᏳᐃ࡟Ꮡᅾࡍࡿ

13

14ࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗࡓࠋࡇࡢࡇ࡜࠿ࡽࠊ⇕Ᏻ1112

10 (ppm)ࣇ ࣮ࣜࡢ DNA Ҹ 1:1 」 ྜయ
య  < Fig.3 1D 1H spectra of GG1 (100 M) with one
ᐃᛶࡣࠊࣇ1:2 」ྜయ࡜࡞ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ
equivalent of ND measured at various temperatures.
ճ ᭱Ᏻᐃᵓ㐀㸦1:2 」ྜయ㸧ࡢゎᯒ
GG1 ࡟ ND ࢆ 2 ᙜ㔞ῧຍࡋ࡚ ᐃࡋࡓ 2D NMR ࢫ࣌ࢡࢺࣝࡢᖐᒓࢆ⾜ࡗࡓࠋู㏵ 15N ᶆ㆑ࡋࡓND ࢆ໬Ꮫྜᡂࡋࠊ1H-15N HSQC

ᐃࢆ⾜࠺ࡇ࡜࡛㸦Fig. 4㸧ࠊࣜ࢞ࣥࢻ⏤᮶ࡢࣆ࣮ࢡࢆྠᐃࡋࡓࠋ

࡞࠾ࠊղࡢ⇕Ᏻᐃᛶࡢ᳨ウ࡟࠾࠸࡚ࠊప

࡛ࡣࣇ࣮ࣜࡢ DNA ࠾ࡼࡧ 1:1 」ྜయࡢࢫ࣌ࢡࢺࣝ࡬ࡢ

ᐤ୚ࡀᠱᛕࡉࢀࡓࡓࡵࠊ❧యᵓ㐀ゎᯒ⏝ࡢ NMRᐃࡣࡍ࡭࡚ 40 Υ࡛⾜ࡗࡓࠋ❧యᵓ㐀ィ⟬ࡢィ⟬᮲௳ࢆ table1 ࡟ࠊィ⟬࡟ࡼࡗ࡚ᚓࡽࢀࡓ」ྜయᵓ㐀ࡢ㔜ࡡྜࢃࡏࢆ Fig.5 ࡟♧ࡋࡓࠋ᭱Ᏻᐃᵓ㐀࡛࠶ࡿ 1:2 」ྜయ࡛ࡣࠊ1 ࡘࡢ d(CGG/CGG)ࣔࢳ࣮ࣇ࡟ᑐࡋ࡚ࠊ㸰ศᏊࡢ ND ࡀ⤖ྜࡋࠊࢩࢺࢩࣥ
ࡢࣇࣜࢵࣉ࢔࢘ࢺࡀ⏕ࡌࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ
G17/6
G18 G7

NP4 NP1

1'
1'

Total distance constraints

NP2 NP3

15N (ppm)

T2/10 T15
T19T20 T14

1H (ppm)

Fig.4 15N-1H HSQC spectra of the 1:2 complex
comprised of GG1 and 15N-labeled ND.

364

Intra residue

90

Inter residue

102

Intermolecular (ND-DNA)

42

H-bond68

Planarity

12

Dihedral constraints

184

RDC

17

G7
G6
C5

G17

G18

RMSDs to mean structure of
the 30 calculated structures
All atom (Å)

1.38 ± 0.32

Back bone (Å)

0.97 ± 0.16

Fig.5
The NMR
structure of the 1:2
GG1-ND complex.

Table 1. Structural statisticsof the 1:2 GG1-ND complex.

մ 㐣Ώⓗᵓ㐀㸦1:1 」ྜయ㸧ࡢゎᯒND ࢆ 1 ➼㔞⁲ୗࡋࡓ≧ែ㸦ࣇ࣮ࣜࡢ DNA ࡜-1.0ᐃࢆ⾜࠸ゎᯒࢆ⾜ࡗࡓࠋ1:2」ྜయ࡛ࡣࠊ5 ␒࠾ࡼࡧ 16 ␒ࡢࢩࢺࢩࣥࡣ஧㔜0㙐࠿ࡽࣇࣜࢵࣉ࢔࢘ࢺࡋ࡚࠸ࡓࡢ࡟ᑐࡋࠊ1:1 」

31P (ppm)

1:1 」ྜయࠊ1:2 」ྜయࡢ 3 ✀ࡀᏑᅾࡍࡿ≧ែ㸧࡛ࠊ஧ḟඖ NMRC
C16ྜయ࡛ࡣࡇࢀࡽࡢࢩࢺࢩࣥࡣࢢ࢔ࢽࣥ࡜ሷᇶᑐ
ࢆᙧᡂࡋ࡚࠸ࡿࡇ࡜ࡀ☜ㄆࡉࢀࡓࠋ1H-31P HSQC
ࢫ࣌ࢡࢺࣝ࡟࠾࠸࡚ࡣࠊ31P ࡢࢣ࣑࢝ࣝࢩࣇࢺࡀ

1.0

5.0

4.5
1H (ppm)－ 160 －

4.0

Fig.6 1H-31P HSQC
spectra of free DNA,
1:1 complex, and 1:2
complex in mixtures.
Peaks derived fromthe 1:1 complex are
indicated by dotted
circles.

㢧ⴭ࡟ప☢ሙࢩࣇࢺࡋࡓ 1:1 」ྜయ⏤᮶ࡢࣆ࣮ࢡࡀぢࡽࢀࡓ㸦Fig.6㸧ࠋࡲࡓ NOESY ࢫ࣌ࢡࢺࣝ୰
࡛ࠊࣇ࣮ࣜࡢ DNA ࡜ 1:1 」ྜయ࡜ࡢ㛫࡛ࡢ໬Ꮫ஺᥮⏤᮶ࡢࣆ࣮ࢡࡀほ ࡉࢀࡓࠋ࠙⪃ᐹࠚձ 㐣Ώⓗᵓ㐀࡜᭱Ᏻᐃᵓ㐀ࡢᏳᐃᛶ࡟ࡘ࠸࡚
⇕Ᏻᐃᛶ࡟㛵ࡋ࡚ࡣࠊࣇ
ࣇ࣮ࣜࡢ DNA Ҹ 1:1 」ྜయ
య < 1:2 」ྜయ࡜࡞ࡗ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡗ
ࡓࠋd(CGG/CGG)ࣔࢳ࣮ࣇ࡟࠾࠸࡚ࠊࣇ࣮ࣜࡢ DNA ࡛ࡣ 2 ࡘࡢ C-G ሷᇶᑐ࡜ 1 ࡘࡢ G-G ࣑ࢫ࣐ࢵࢳሷᇶᑐࡀᙧᡂࡉࢀ࡚࠸ࡿࡀࠊ1:1 」ྜయ࡛ࡣ 2 ࡘࡢ C-G ሷᇶᑐ࡜ 2 ࡘࡢ G-NP ሷᇶᑐࡀࠊࡲࡓ
1:2 」ྜయ࡛ࡣ 4 ࡘࡢ G-NP ሷᇶᑐࡀᙧᡂࡉࢀ࡚࠸ࡿࠋࣜ࢞ࣥࢻࡢ⤖ྜ࡟࠾࠸࡚ࡣࠊ୙Ᏻᐃ࡞ G-G࣑ࢫ࣐ࢵࢳሷᇶᑐࡀゎᾘ࠾ࡼࡧࠊ᪂ࡓ࡞ NP̾ࢢ࢔ࢽࣥ㛫ࡢỈ⣲⤖ྜᙧᡂࡀᐤ୚ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋຍ࠼࡚ࠊࢼࣇࢳࣜࢪࣥ⎔ࡣ 2 ࡘࡢ 6 ဨ⎔࠿ࡽ࡞ࡿ 2 ⎔ᘧ໬ྜ≀࡛࠶ࡿࡓࡵࠊ๓ᚋࡢሷᇶ࡜
ࡢࢫࢱࢵ࢟ࣥࢢࡀ᭷฼࡛࠶ࡿࡇ࡜ࡶ」ྜయᏳᐃ໬࡟ᐤ୚ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ
1:1 」ྜయ࡜ 1:2 」ྜయ࡛ࡣࠊሷᇶᑐࡢᩘࡣྠࡌ࡛࠶ࡿࡀࠊࣜࣥ㓟㦵᱁࡟⏕ࡌࡿṍࡳࡢ኱ࡁࡉࡀ
␗࡞ࡿࠋ1:1 」ྜయ࡛ࡣ ND ࡢᤄධ࡟క࠸ࠊࣜ࢞ࣥࢻ⤖ྜ㒊఩ࡢࣜࣥ㓟ࢪ࢚ࢫࢸࣝ⤖ྜࡀᘬࡁఙࡤ
ࡉࢀࡿࠋ୍᪉࡛ࠊ1:2 」ྜయ࡛ࡣࢩࢺࢩࣥࡀࣇࣜࢵࣉ࢔࢘ࢺࡋ࡚࠸ࡿࡓࡵࠊࣜࣥ㓟㦵᱁ࡢṍࡳࡀ⵳✚ࡀ㜵ࡀࢀ࡚࠸ࡿࠋࡑࡢࡓࡵࠊ1:2 」ྜయࡣ 1:1 」ྜయ࡟ẚ࡭࡚⇕ⓗ࡟Ᏻᐃ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ
ᐇ㝿࡟ 1H-31P HSQC ࢫ࣌ࢡࢺࣝ࡟࠾࠸࡚ࠊ1:1 」ྜయ࡛ࡣ 31P ࡢ㢧ⴭ࡞ప☢ሙࢩࣇࢺࡀぢࡽࢀ࡚࠾ࡾࠊࣜࣥ㓟㦵᱁ࡀᶆ‽ⓗ࡞ᵓ㐀࠿ࡽ㐓⬺ࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀ࡚࠸ࡿࠋ
ᶆ NDࡢ
ࡢDNAㄆ
ㄆ㆑࣓࢝ࢽࢬ࣒
」ྜయࡢ⤖ྜᵝᘧ࠾ࡼࡧ᝿ᐃࡉࢀࡿDNAㄆ㆑ᶵᵓࢆFig.7࡟♧ࡋࡓࠋNOESYࢫ࣌ࢡࢺࣝ࡟࠾࠸࡚ࣇ
࣮ࣜࡢDNA࡜1:1」ྜయ࡜ࡢ㛫࡛஺᥮ࣆ࣮ࢡࡀほࡉࢀࡓࡇ࡜࠿ࡽࠊࣇ࣮ࣜࡢDNA࡜1: 1」ྜయ࡜ࡢά
ᛶ໬㞀ቨࡣపࡃࠊ㏿ࡸ࠿࡟1:1」ྜయ࡬⛣⾜ࡍࡿ࡜⪃࠼ࡽࢀࡿࠋ࢖ࣥࢱ࣮࣮࢝ࣞࢱ࣮ࡢ๓ᚋࡢ࣡ࢺࢯ
ࣥ-ࢡࣜࢵࢡሷᇶᑐࡣ୙Ᏻᐃ࡟࡞ࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠾ࡾࠊ1:1」ྜయ࡟࠾࠸࡚ࡶྠᵝ࡟ࠊG-NPሷᇶᑐࡢ๓ᚋࡢC-Gሷᇶᑐࡣ୙Ᏻᐃ࡟࡞ࡗ࡚࠸ࡿ࡜ண᝿

Fig.7 The schematic illustration of binding
mode and binding process of the 1:1 and 1:2
GG1-ND complex.

ࡉࢀࡿࠋࡇࡢ୙Ᏻᐃ࡞C-Gሷᇶᑐ࡟ᑐࡋ2ศᏊ┠ࡢ
NDࡀᤄධࡋᵓ㐀ኚ໬ࡀ㉳ࡇࡿࡇ࡜࡟ࡼࡗ࡚ࠊ᭱⤊ⓗ࡟᭱Ᏻᐃ࡞1:2」ྜయࡀ⏕ࡌࡿ࡜⪃࠼ࡽࢀࡿࠋ
࠙⤖ㄽࠚd(CGG/CGG)㓄ิࢆㄆ㆑ࡍࡿ⸆๣ND࡜DNAࡢ┦஫స⏝ࢆNMR࡟ࡼࡗ࡚ゎᯒࡋࡓࠋ᭱Ᏻᐃ࡞1:2」ྜయ࡟ຍ࠼ࠊ㐣Ώⓗ࡟ᙧᡂࡉࢀࡿ1:1」ྜయࡢࡑࢀࡒࢀࡢ❧యᵓ㐀ࠊ⇕Ᏻᐃᛶ࠾ࡼࡧ໬Ꮫ஺᥮ࢆ
ゎᯒࡋࠊ⸆๣࡟ࡼࡿDNAࡢㄆ㆑࣓࢝ࢽࢬ࣒ࢆ⪃ᐹࡋࡓࠋ࠙ཧ⪃ᩥ⊩ࠚ
(1) Nakamori, M., et al. (2020) A slipped-CAG DNA-binding small molecule induces trinucleotide-repeat

contractions in vivo. Nat. Genet. 52, 146–159.
(2) Nakatani, K., et al. (2001) Recognition of guanine-guanine mismatches by the dimeric form of 2-amino1,8-naphthyridine. J. Am. Chem. Soc. 123, 12650–12657.

－ 161 －

P15

᪻⹸⣽⬊Ⓨ⌧⣔࡟࠾ࡅࡿ࢔ࣛࢽࣥ㑅ᢥᶆ㆑ἲࡢ㛤Ⓨ‫ۑ‬ᖾ⚟⿱㸪ᶓ⁁ᬛ㈗1㸪௒஭㥴㍜1㸪ⓑ▼ຬኴ㑻1㸪஬༑ᔒಇ௓2㸪ᒣཱྀ⚽ᖾ
2㸪Ỉ㉺฼ᕭ2㸪㕥ᮌᴿ୍㑻2,3㸪ᔱ⏣୍ኵ11ᮾி኱Ꮫ࣭኱Ꮫ㝔⸆Ꮫ⣔◊✲⛉2࿡ࡢ⣲ᰴᘧ఍♫3♫ᅋἲே᪥ᮏࣂ࢖࢜⏘ᴗ᝟ሗ໬ࢥࣥࢯ࣮ࢩ࢔࣒

Deuteration and selective labeling of alanine methyl groups of ȕ 2-adrenergic receptor
expressed in a baculovirus-insect cell expression system‫ۑ‬Yutaka Kofuku1, Tomoki Yokomizo1 Shunsuke Imai1 Yutaro Shiraishi1 Shunsuke Igarashi2, Hideyuki
Yamaguchi2, Toshimi Mizukoshi2, Ei-ichiro Suzuki2,3Takumi Ueda1 Ichio Shimada1
1 Graduate School of Pharmaceutica Sciences The University of Tokyo
2 Institute for Innovation, Ajinomoto Co., Inc.
3 Japan Biological Informatics Consortium (JBiC)

G protein-coupled receptors (GPCRs) exist in equilibrium between multiple conformations, and their
populations and exchange rates determine their functions. However, analyses of the conformational
dynamics of GPCRs in lipid bilayers are still challenging, because methods for observations of NMR
signals of large proteins expressed in a baculovirus-insect cell expression system (BVES) are limited. Here,
we report a method to incorporate methyl-13C1H3-labeled alanine with > 45% efficiency in highly
deuterated proteins expressed in BVES. Application of the method to
the NMR observations of ȕ2-adrenergic receptor in micelles and in
nanodiscs revealed the ligand-induced conformational differences
throughout the transmembrane region of the GPCR.
Gࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయ(GPCR)ࡣ㸪┿᰾⏕≀᭱኱ࡢ⭷ࢱ
ࣥࣃࢡ㉁ࣇ࢓࣑࣮࡛ࣜ࠶ࡾ㸪ከࡃࡢ⏕⌮ᶵ⬟࡟㛵୚ࡍࡿ௚㸪๰⸆ᶆⓗ࡜ࡋ࡚ࡶ㔜せ࡛࠶ࡿ㸬㏆ᖺࡢNMRゎᯒ࡞࡝࡟ࡼࡾ㸪
GPCRࡣ」ᩘࡢᵓ㐀㛫ࢆ஺᥮ࡍࡿືⓗᖹ⾮≧ែ࡟࠶ࡾ㸪ࡑࡢᖹ
⾮ࡢࢩࣇࢺࡣ㸪ࢩࢢࢼࣝఏ㐩࡞࡝ࡢᶵ⬟ࢆไᚚࡍࡿࡇ࡜ࡀ᫂
ࡽ࠿࡟࡞ࡗ࡚ࡁࡓ1㸬୍᪉࡛㸪GPCRࡢⓎ⌧࡟ࡣ᪻⹸⣽⬊㸫ࣂ࢟ࣗࣟ࢘࢖ࣝࢫⓎ⌧⣔(BVES)ࡀᚲせ࡛࠶ࡿࡇ࡜࠿ࡽ㸪Ᏻᐃྠ఩యᶆ㆑ἲ࡟ไ㝈ࡀ࠶ࡾ㸪⬡㉁஧㔜⭷୰ࡢGPCRࡢᵓ㐀ᖹ⾮ࢆ㧗࠸✵㛫ศゎ⬟࡛ゎᯒࡍࡿࡇ࡜ࡣᅔ㞴࡛࠶ࡿ㸬ࡇࢀࡲ࡛㸪ᡃࠎࡣ㸪BVES࡟࠾ࡅࡿ㧗ᗘ࡞㔜Ỉ⣲໬࡜࣓ࢳ࢜ࢽ࣓ࣥࢳࣝᇶ

Fig.

1.

Alanine-selective

13C1H -labeling of thioredoxin
3

with deuteration in BVES.
1H-13C

HSQC

spectraof㑅ᢥⓗ࡞13C1H3ᶆ㆑ࢆ㛤Ⓨࡋ㸪GPCRࡢNMRゎᯒ࡟㐺⏝ࡋ࡚ࡁthioredoxin expressed in BVESࡓ2㸬ᮏ◊✲࡛ࡣ㸪ࡇࢀ࡟ຍ࠼࡚㸪࢔ࣛࢽ࣓ࣥࢳࣝᇶࡢ㑅ᢥⓗwith two different protocols.

࡞13C1H3ᶆ㆑ࡀྍ⬟࡞᪉ἲࢆ☜❧ࡋࡓ3㸬Ᏻᐃྠ఩యᶆ㆑㸪᪻⹸⣽⬊Ⓨ⌧⣔㸪⭷ࢱࣥࣃࢡ㉁‫࠿ࡓࡺࡃࡩ࠺ࡇۑ‬㸪ࡼࡇࡳࡒ࡜ࡶࡁ㸪࠸ࡲ࠸ࡋࡹࢇࡍࡅ㸪ࡋࡽ࠸ࡋࡺ࠺ࡓࢁ࠺㸪࠸ࡀࡽࡋࡋࡹࢇ
ࡍࡅ㸪ࡸࡲࡄࡕࡦ࡛ࡺࡁ㸪ࡳࡎࡇࡋ࡜ࡋࡳ㸪ࡍࡎࡁ࠼࠸࠸ࡕࢁ࠺㸪࠺࠼ࡔࡓࡃࡳ㸪ࡋࡲࡔ࠸ࡕ࠾

－ 162 －

࣓ࢳࣝTROSYἲࢆ⏝࠸࡚㸪࢔ࣛࢽࣥࡢ࣓ࢳࣝᇶ⏤᮶ࡢNMRࢩࢢࢼࣝࢆ㧗ឤᗘ࡟ほ ࡍࡿ࡟ࡣ㸪࢔ࣛࢽ࣓ࣥࢳࣝᇶࡀ㧗࠸ᶆ㆑⋡࡛13C1H3ᶆ㆑ࡉࢀ࡚࠸
ࡿࡇ࡜࡟ຍ࠼࡚㸪࢔ࣛࢽࣥĮ఩ࡀ㧗ᗘ࡟2Hᶆ㆑ࡉࢀࡿࡇ࡜ࡀ㔜せ࡛࠶ࡿ㸬BVES࡟࠾࠸࡚ࡣ㸪᪻⹸⣽⬊ࡣ㧗⃰ᗘࡢ㔜Ỉ୰࡛ࡣ⏕⫱ࡋ࡞࠸ࡇ࡜࠿ࡽ㸪㍍Ỉ
ࢆ⏝࠸ࡓᇵᆅࡀᚲせ࡛࠶ࡿ㸬ࡇࡢ᫬ࠊ⣽⬊ෆࡢࢺࣛࣥࢫ࢔࣑ࢼ࣮ࢮάᛶ࡟ࡼࡾ㸪Į఩ࡀ2H࠿ࡽ1H࡟ᡠ
ࡗ࡚ࡋࡲ࠺ࡇ࡜ࡀㄢ㢟࡛࠶ࡗࡓ㸬ࡑࡇ࡛㸪ࣉࣟࢺࢥࣝࡢ᭱㐺໬ࢆ࠾ࡇ࡞࠸㸪Ᏻᐃྠ఩యᶆ㆑࢔ࣛࢽ
ࣥ࡜ࢺࣛࣥࢫ࢔࣑ࢼ࣮ࢮ㜼ᐖ๣ࢆ㸪ࣂ࢟ࣗࣟ࢘࢖
ࣝࢫឤᰁᚋ20᫬㛫࡛ῧຍࡍࡿࡇ࡜࡜ࡋࡓ㸬ࡇࡢ᮲௳࡛ࡣ㸪࢔ࣛࢽ࣓ࣥࢳࣝᇶࡢ13C1H3ᶆ㆑⋡ࡀ46%࡛
࠶ࡾ㸪ࡑࡢ࠺ࡕĮ఩ࡀ2Hᶆ㆑ࡉࢀࡓ๭ྜࡀ92%࡛࠶
ࡿࡇ࡜࠿ࡽ㸪㧗ឤᗘほ ࡟༑ศ࡞ᶆ㆑⋡࡛࠶ࡿ࡜⤖ㄽࡋࡓ(Fig. 1)㸬

Fig. 2. Observations of ȕ2AR alanine
resonances in nanodisc lipid bilayers.
1H-13CHMQC spectrum of alanine- andmethionine-selective 13C1H3-labeled ȕ2AR in
lipid bilayers of nanodisc, boud with aninverse agonist, carazolol.

ࡇࡢᡭἲࢆ⏝࠸࡚㸪GPCRࡢ୍✀࡛࠶ࡿȕ2-࢔ࢻࣞࢼࣜࣥཷᐜయ(ȕ2AR)ࡢNMRゎᯒࢆ࠾ࡇ࡞ࡗ
ࡓ㸬14✀㢮ࡢ࢔࣑ࣀ㓟ṧᇶࢆ2Hᶆ㆑ࡋ㸪࣓ࢳ࢜ࢽࣥ࡜࢔ࣛࢽࣥࡢ࣓ࢳࣝᇶ࡟㑅ᢥⓗ࡟13C1H3ᶆ㆑
ࢆᑟධࡋࡓヨᩱࢆㄪ〇ࡋ㸪ࢼࣀࢹ࢕ࢫࢡࡢ⬡㉁஧㔜⭷୰࡟෌ᵓᡂࡋࡓୖ࡛㸪1H-13C HMQCࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓ㸬ࡑࡢ⤖ᯝ㸪࣓ࢳ࢜ࢽ࣓ࣥࢳࣝᇶࡢNMRࢩࢢࢼࣝ࡟ຍ࠼࡚㸪22ṧᇶࡢ࢔ࣛࢽࣥ
ṧᇶ࡟ᴫࡡᑐᛂࡍࡿᩘࡢNMRࢩࢢࢼࣝࡀほ ࡉࢀࡓ(Fig. 2)㸬ࡇࡢࡇ࡜࠿ࡽ㸪ᮏᡭἲࢆᣢࡕࡿࡇ࡜࡛㸪⭷㈏㏻㡿ᇦࢆྵࡵࡓȕ2ARࡢศᏊ඲య࠿ࡽᵓ㐀᝟ሗࢆᚓࡿࡇ࡜ࡀ࡛ࡁࡿ࡜⤖ㄽࡋࡓ㸬ᮏᡭἲࡣ㸪⣙300 kDa࡟┦ᙜࡍࡿ㸪ࢼࣀࢹ࢕ࢫࢡ୰ࡢGPCR࡟ࡶ㐺⏝ྍ⬟࡛࠶ࡿࡇ࡜࠿ࡽ㸪௚ࡢከࡃࡢ
┿᰾⏕≀⏤᮶⭷ࢱࣥࣃࢡ㉁ࡢNMRゎᯒ࡟᭷ຠ࡛࠶ࡿ࡜⪃࠼࡚࠸ࡿ㸬
References(1) Shimada, I. et al. (2019) GPCR drug discovery: integrating solution NMR data with crystal and cryo-EM

structures. Nat Rev Drug Discov 18, 59–82.
(2) Kofuku, Y. et al. (2014) Functional dynamics of deuterated ȕ2-adrenergic receptor in lipid bilayers

revealed by NMR spectroscopy. Angew Chem Int Ed Engl 53, 13376–13379.
(3) Kofuku, Y. et al. (2018) Deuteration and selective labeling of alanine methyl groups of ȕ2-adrenergic
receptor expressed in a baculovirus-insect cell expression system. J Biomol NMR 71, 185–192.

－ 163 －

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P17

ᐃ㔞NMR⏝ㄆドᶆ‽≀㉁(ࣇࢱࣝ㓟Ỉ⣲࣒࢝ࣜ࢘, NMIJ CRM 4603-a)ࡢ㛤Ⓨ‫ۑ‬ᒣ㷂ኴ୍ࠊΎỈ⏤㝯ࠊ໭∾♸Ꮚࠊ୰ᮧဴᯞࠊ㩚᪂ດࠊఀ⸨ಙ㟹⏘ᴗᢏ⾡⥲ྜ◊✲ᡤ࣭≀㉁ィ ᶆ‽◊✲㒊㛛Development of certified reference material for quantitative NMR(Potassium hydrogen phthalate, NMIJ CRM 4603-a)‫ۑ‬Taichi Yamazaki, Yoshitaka Shimizu, Yuko Kitamaki, Satoe Nakamura, Xinnu Bao and Nobuyasu Ito
National Institute of Advanced Industrial Science and Technology (AIST) / Research Institute for Material
and Chemical Measurement
Quantitative NMR can be quantified based on atomic nuclei, so it is possible to obtain quantitativevalues with metrological traceability by using a reference material different from the substance to bemeasured. Until now, certified reference materials of potassium hydrogen phthalate (PHP) (NMIJ CRM
3001-c, NIST SRM 84l, etc.), which are highly water-soluble, have been widely used in quantitative NMR
using heavy water as the solvent, but the certified purity is not the "purity as acid" used in quantitative NMR.
However, certified purity is the "purity as acid" used in the quantitative NMR. However, certified purity is
not the mass fraction used in quantitative NMR such as "purity as acid. Therefore, it was not recommended
to use it strictly as a reference material for quantitative NMR. So, we developed NMIJ CRM 4603-a as acertified reference material for quantitative NMR with PHP purity as the certified value. In this presentation,
we will introduce the details of the evaluation method to determine the certified value in this certified
reference material.
ᐃ㔞 NMR ࡣཎᏊ᰾ࢆᇶ‽࡟ᐃ㔞࡛ࡁࡿࡓࡵ㸪 ᐃᑐ㇟≀㉁࡜ࡣ␗࡞ࡿᶆ‽≀㉁ࢆ฼⏝ࡋ࡚㸪ィ㔞ィ ࢺ࣮ࣞࢧࣅࣜࢸ࢕ࡀ☜ಖࡉࢀࡓᐃ㔞್ࢆᚓࡿࡇ࡜ࡀ࡛ࡁࡿศᯒἲ࡜ࡋ࡚ᬑཬࡋ㸪JIS ࡸ᪥ᮏ⸆ᒁ᪉࡞࡝ࡢබᐃἲ࡛ࡶ฼⏝ࡉࢀ࡚ࡁ࡚࠸ࡿ㸬୍᪉㸪ᐃ㔞 NMR ࡛⏝࠸ࡽࢀࡿᶆ‽≀㉁࡟ࡣ㸪㧗⣧ᗘ࡛ከᵝ࡞⁐፹࡬ࡢ⁐ゎᛶࡸ␗࡞ࡿ໬Ꮫࢩࣇࢺ್ࢆᣢࡘࡶࡢ࡞࡝ࠊ」ᩘ✀㢮ࡢᶆ‽≀㉁ࡀ౪⤥ࡉࢀ࡚࠸ࡿࡇ࡜ࡀᮃࡲࡋ࠸㸬ᙜࢢ࣮ࣝࣉ࡛ࡣ㸪᭷ᶵ⁐፹⣔ࡢᶆ‽≀㉁࡜ࡋ࡚ 3,5-ࣅࢫ(ࢺࣜࣇ࣓ࣝ࢜ࣟࢳࣝ)Ᏻᜥ㤶㓟(NMIJ CRM 4601)࡜ 1,4-ࣅࢫࢺ࣓ࣜࢳࣝࢩࣜࣝ-2,3,5,6-ࢸࢺࣛࣇࣝ࢜ࣟ࣋ࣥࢮࣥ(NMIJ CRM 4602)ࢆ㛤Ⓨࡋ࡚ࡁࡓ㸬ࡋ࠿ࡋ㸪ࡇࢀࡽࡢ≀㉁ࡣỈ⁐ᛶࡀపࡃ㸪Ỉ⣔ࡢศᯒ࡛ࡣ฼⏝ࡍࡿࡇ࡜ࡀ㞴ࡋ࠸࡜࠸࠺ㄢ㢟ࡀ࠶ࡗࡓ㸬㔜Ỉࢆ⁐፹࡜ࡋࡓᐃ㔞 NMR ࡛ࡣ㸪Ỉ⁐ᛶࡢ㧗࠸ࣇࢱࣝ㓟Ỉ⣲࣒࢝ࣜ࢘(PHP)ࡢㄆドᶆ‽≀㉁㸦NMIJ CRM 3001-cࠊNIST SRM 84l ➼㸧ࡀᶆ‽≀㉁࡜ࡋ࡚ᗈࡃ
฼⏝ࡉࢀ࡚࠸ࡓࡶࡢࡢ㸪ㄆドࡉࢀ࡚࠸ࡿ⣧ᗘࡣ㸪ࠕ㓟࡜ࡋ࡚ࡢ⣧ᗘࠖ࡞࡝ᐃ㔞 NMR ࡛౑⏝ࡉࢀࡿ㉁㔞ศ⋡࡞࡝࡛ࡣ࡞࠸ࡓࡵ㸪ཝᐦ࡟ࡣᐃ㔞 NMR ⏝ࡢᶆ‽≀㉁࡜ࡋ࡚⏝࠸ࡿࡇ࡜ࡀ᥎ዡࡉࢀ࡚࠸
࡞࠿ࡗࡓ㸬ࡇࡢࡓࡵ㸪௒ᅇ㸪ᐃ㔞 NMR ⏝ㄆドᶆ‽≀㉁࡜ࡋ࡚㸪PHP ⣧ᗘࢆㄆド್࡜ࡋࡓ NMIJ
CRM 4603-a ࢆ㛤Ⓨࡋࡓ㸬ᮏⓎ⾲࡛ࡣ㸪ㄆド್Ỵᐃࡢࡓࡵࡢホ౯᪉ἲࡢヲ⣽࡟ࡘ࠸࡚⤂௓ࡍࡿ㸬ᐃ㔞NMRࠊㄆドᶆ‽≀㉁ࠊࣇࢱࣝ㓟Ỉ⣲࣒࢝ࣜ࢘żࡸࡲࡊࡁࡓ࠸ࡕ㸪ࡋࡳࡎࡼࡋࡓ࠿㸪ࡁࡓࡲࡁࡺ࠺ࡇ㸪࡞࠿ࡴࡽࡉ࡜࠼㸪ࡤ࠾ࡋࢇࡠ㸪࠸࡜࠺ࡢࡪ
ࡸࡍ－ 166 －

㛤 Ⓨ ࡋ ࡓ NMIJ
CRM 4603-a ࡢ ⣧ᗘỴᐃࢫ࣮࣒࢟
ࢆFig. 1࡟♧ࡍ㸬ᮏᶆ‽≀㉁ࡢ⣧ᗘ
ᐃ࡟ࡣ2ࡘࡢ
ᐃࢆ⏝࠸ࡓ㸬ࡲࡎ㸪㢮ఝ᭷ᶵ୙⣧≀㸪ṧ␃⁐፹㸪↓ᶵᡂศ㸪Ỉศ➼ࡢᚤ㔞࡞୙⣧≀ࢆಶࠎ࡟ᐃ㔞ࡋ࡚㸪

Fig. 1. Scheme of purity assessment for determination of certified values

1 kg/kg ࠿ ࡽ ᕪ ࡋᘬࡃࡇ࡜࡛⣧ᗘࢆỴᐃࡍࡿᕪᩘἲ࡟ࡼࡗ࡚Ỵᐃࡋࡓ⣧ᗘࢆ1ࡘ┠ࡢ⣧ᗘ࡜ࡋ࡚⏝࠸ࡓ㸬ࡲࡓ㸪㟁㔞⁲ᐃ࡟ࡼࡿ㓟࡜ࡋ࡚⟬ฟࡋࡓ⣧ᗘ࡜࣒࢝ࣜ࢘࠾ࡼࡧࢼࢺ࣒ࣜ࢘ࢆᐃ㔞ࡋ࡚᥎ᐃࡋࡓࣇࢱࣝ㓟࢖࢜ࣥ࡜ࡋ࡚ࡢ⣧ᗘ࠿ࡽỴᐃࡋࡓ⣧ᗘࢆ2ࡘ┠ࡢ⣧ᗘ್࡜ࡋ࡚⏝࠸ࡓ㸬ࡇࡢᕪᩘἲ࡟ࡼࡿ⣧ᗘ࡜ࣇࢱࣝ
㓟࢖࢜ࣥ࡜ࡋ࡚ࡢ⣧ᗘࡢ┦ຍᖹᆒ್(0.9998 kg/kg)ࢆࣇࢱࣝ㓟Ỉ⣲࣒࢝ࣜ࢘ࡢ⣧ᗘ࡜ࡋࡓ㸬ࡲࡓ㸪⣧ᗘ್࡟ᑐࡍࡿィ㔞ィࢺ࣮ࣞࢧࣅࣜࢸ࢕ࢆ☜ಖࡍࡿࡓࡵ࡟㸪⣧ᗘỴᐃ࡟࠾ࡅࡿ୙☜࠿ࡉࡢホ౯ࢆ⾜ࡗࡓ㸬⣧ᗘࡢྜᡂᶆ‽୙☜࠿ࡉ࡟ࡣ㸪ྛ⣧ᗘホ౯ἲཬࡧࡑࡢ᪉ἲ㛫ᕪ㸪ᆒ㉁ᛶ㸪Ᏻᐃᛶ࡟㉳ᅉࡍࡿ୙☜࠿ࡉࢆྜᡂࡋ࡚ぢ✚ࡶࡾ㸪ㄆド್ࢆ
(0.9998±0.0003) kg/kg (ໟྵಀᩘ, k=2)࡜Ỵᐃࡋࡓ㸬
Fig.2࡟ࡣ㛤ⓎࡋࡓNMIJ CRM 4603-a ࢆ♧ࡍ㸬᪤Ꮡࡢᐃ㔞NMR⏝ㄆドᶆ‽≀㉁ࢆᇶ‽࡟ࡋࡓᮏࣇ
ࢱࣝ㓟Ỉ⣲࣒࢝ࣜ࢘ࡢ⣧ᗘᐃ್ࡣ㸪

(0.9997±0.0006) kg/kg (ໟྵಀᩘ, k=2)࡛࠶ࡾ㸪ㄆド್࡜Ⰻዲ࡟୍⮴ࡋࡓࡇ࡜࠿ࡽㄆド್ࡢጇᙜᛶࡀ
☜ㄆࡉࢀࡿ࡜࡜ࡶ࡟ᐃ㔞NMR⏝ࡢᶆ‽≀㉁࡜ࡋ
࡚⏝࠸࡚ࡶၥ㢟࡞࠸ࡇ࡜ࢆ☜ㄆࡍࡿࡇ࡜ࡀ࡛ࡁ
ࡓ㸬

Fig. 2. Certified reference material for
quantitative NMR (Potassium hydrogen
phthalate, NMIJ CRM 4603-a)－ 167 －

P18Y

ග↷ᑕ⁐ᾮNMRᢏ⾡ࢆ⏝࠸ࡓࣉࣟࢺ࣏ࣥࣥࣉᆺࣟࢻࣉࢩࣥRxRࡢ
ᬯ≧ែ࠾ࡼࡧග཯ᛂࢧ࢖ࢡࣝ୰㛫య࡟࠾ࡅࡿᵓ㐀≉ᛶゎᯒ‫ۑ‬㕥ᮌ㔛ె㸪ᘅす㯇ຍ㸪ᑠᓥ្୍㸪㡲⸨㞝Ẽ㸪㛗ᓥᩄ㞝㸪ᒣᓮಇኵ㸪㧗ᶫᰤኵ
1.ᶓ὾ᕷ❧኱Ꮫ኱Ꮫ㝔 ⏕࿨་⛉Ꮫ◊✲⛉
2.ᒸᒣ኱Ꮫ኱Ꮫ㝔 Ꮫ⾡◊✲㝔་ṑ⸆ᇦ ⸆Ꮫ⣔
3.⌮໬Ꮫ◊✲ᡤ ⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮

Structural characterization of Rubrobacter xylanophilus rhodopsin RxR in the unphotolyzed stateand photointermediates using photo-irradiation solution state NMR spectroscopy‫ۑ‬Rika Suzuki1, Reika Hironishi1, Keiichi Kojima2, Yuki Sudo2, Toshio Nagashima3, Toshio Yamazaki3,
Hideo Takahashi1
1Graduate School of Medical Life Science, Yokohama City University

2

Medicine, Dentistry and Pharmaceutical Sciences, Institute of Academic Research, Okayama University

3

RIKEN, Center for Biosystems Dynamics Research
Exchangeable protons and their relating hydrogen bonds play important roles in structures and functionsof biomolecules. However, it is not easy to directly observe them especially in the case that those protons
are under rapid hydrogen exchange with solvent water, such as oxygen-bound protons. Therefore, NMR
structural analyses for oxygen-bound protons were limited so far.
In this study, we employed light-driven proton-pumping rhodopsin from the eubacterium Rubrobacter
xylanophilus, RxR, showing high stability against heat and chromophore retinal as a target molecule, andutilized the solution NMR approaches to obtain local structural information about the hydrogen bonding
network around the retinal Schiff base on the unphotolyzed (dark-adapted) state and the light-adapted state(photointermediates). 1H NMR spectra showed three exchangeable proton resonances originating from
Y49, D108, and Y178 for the unphotolyzed state of RxR, which means that those OHs are buried andinvolved in stable hydrogen bonds. The utilization of photo-irradiation NMR approaches clarified thecorrelation between RxR in the unphotolyzed state and photointermediates. These results insisted hydrogenbonds related to Y49 and Y178 and the strong interaction between W75 and D205 in the light-adapted state
were critical for the RxR activity.
[Introduction]⏕యศᏊࡢᵓ㐀⥔ᣢ࡜ࡑࡢᶵ⬟Ⓨ⌧࡟ࡣࠊࢱࣥࣃࢡ㉁୰ࡢ஺᥮ᛶỈ⣲ࡀ㛵୚ࡍࡿỈ⣲⤖ྜࡸࡑࡢኚ໬ࡀ㔜せ࡞ᙺ๭ࢆᯝࡓࡍࠋ୍᪉࡛ࠊࡇࢀࡽ஺᥮ᛶỈ⣲ࡣࠊࣔࣝ༢఩࡛ᏑᅾࡍࡿࣂࣝࢡỈ࡜஺᥮ࡍࡿࡓࡵࠊࡑࡢ஺᥮㏿ᗘࡢዴఱ࡟ࡼࡗ࡚ࡣࠊࡑࢀࡽࢆ┤᥋ⓗ࡟ほ ࡍࡿࡇ࡜ࡣᐜ࡛᫆ࡣ࡞࠸ࠋ⁐ᾮ1H-NMR ᐃ࡛ࡣࠊࣂࣝࢡỈ࡜ࡢ஺᥮ࡀᢚไࡉࢀ࡚࠸ࡿ࢔࣑ࢻỈ⣲ࢆ᳨ฟࡍࡿ◊✲ࡣ┒ࢇ࡟⾜ࢃࢀ࡚࠸ࡿࡀࠊ㓟⣲ཎᏊ࡟⤖ྜࡋࡓỈ⣲ཎᏊ㸦OH / COOH㸧࡟ࡘ࠸࡚ࡣࠊࡑࡢ㏿࠸஺᥮㏿ᗘࡢࡓࡵ┤᥋ほ ࡣᐜ࡛᫆࡞ࡃࠊศᏊෆ㒊࡛Ỉ⣲⤖ྜࢆᙧᡂࡋ࡚࠸ࡿỈ⣲ཎᏊࢆ᳨ฟࡋࡓ◊✲ሗ࿌ࡀ⭷ࢱࣥࣃࢡ㉁㸪⁐ᾮNMRἲ㸪ග↷ᑕNMRᢏ⾡‫࠿ࡾࡁࡎࡍۑ‬㸪ࡦࢁ࡟ࡋࢀ࠸࠿㸪ࡇࡌࡲࡅ࠸࠸ࡕ㸪ࡍ࡝࠺ࡺ࠺ࡁ㸪࡞ࡀࡋࡲ࡜ࡋ࠾㸪ࡸࡲࡊࡁ࡜ࡋ࠾㸪ࡓ࠿ࡣࡋࡦ࡛࠾

－ 168 －

ᩘ౛Ꮡᅾࡍࡿࡢࡳ࡛࠶ࡿ1,2ࠋᮏ◊✲࡛ࡣࠊዲ⇕┿ṇ⣽⳦Rubrobacter xylanophilus⏤᮶࡛ࠊග㥑ືࣉ
ࣟࢺࣥ㍺㏦άᛶࢆ᭷ࡍࡿࣟࢻࣉࢩࣥRxR 3ࢆゎᯒᑐ㇟࡜ࡋࠊRxRࡢᬯ≧ែࠊ࠾ࡼࡧග཯ᛂ୰㛫య࡟࠾ࡅࡿỈ⣲⤖ྜࢿࢵࢺ࣮࣡ࢡ࡟㛵ࢃࡿ஺᥮ᛶỈ⣲ࡢ᳨ฟࢆ୰ᚰ࡜ࡍࡿᒁᡤᵓ㐀ゎᯒࢆ⾜࠸ࠊRxRࡢᶵ⬟Ⓨ⌧࡟㛵ࢃࡿᵓ㐀≧ែࡢゎ᫂࡜ࠊࡑࡢᵓ㐀⥔ᣢ࡟㛵୚ࡍࡿṧᇶࡢᙺ๭ࢆ⌮ゎࡍࡿࡇ࡜ࢆ┠ᣦࡋࡓࠋ
[Results and Discussion]
1㸬ศᏊෆ㒊࡟ᏑᅾࡍࡿỈ⣲⤖ྜࢆᙧᡂࡍࡿ OH/COOH ⏤᮶ࢩࢢࢼࣝࡢほ⏺㠃άᛶ๣ ȕOG ࡛ྍ⁐໬ࡋࡓ 15N ᶆ㆑
RxR ࡢ¹H-NMR

ᐃࢆ 45ႏ࡛⾜ࡗࡓ࡜ࡇࢁࠊ11Ң12 ppm ࡢప☢ሙ࡟ࢩࢢࢼࣝࡀ 2 ࡘ
ࡉࢀࡓ (Fig. 1A)ࠋ15N-filtered ¹H-NMR

ほᐃࢆ⾜ࡗࡓ࡜ࡇࢁࠊࡉࡽ࡟ 9.6 ppm ࡟ࢩࢢࢼࣝࡀ 1 ࡘほ ࡉࢀࡓ (Fig.1B)ࠋ໬Ꮫࢩ
ࣇࢺ್ࡼࡾࠊࡇࢀࡽࡢࢩࢢࢼࣝࡣ OH ᇶࠊࡲࡓࡣ COOH ᇶ⏤᮶ࡢࢩࢢࢼ࡛ࣝ࠶ࡿྍ
⬟ᛶࡀ⪃࠼ࡽࢀࡓࠋ ࢔࣑ࣀ㓟ṧᇶ⨨᥮యࢆ⏝࠸ࡓNMRゎᯒ࡟ࡼࡾࠊࡑࢀࡽࡢࢩࢢࢼࣝࡣࣞࢳࢼ࣮ࣝ㏆

Fig. 1 1D NMR spectra of [15N] RxR in ȕ-OG micelles.
(A) ¹H-NMR spectrum.
(B) 15N-filtered ¹H-NMR spectrum.

ഐࡢỈ⣲⤖ྜࢿࢵࢺ࣮࣡ࢡ (Fig. 2) ࡟㛵୚ࡍࡿY49ࠊY178࡜ࡑࡢ㏆ഐ࡟Ꮡᅾࡍࡿ
D108⏤᮶࡛࠶ࡿࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗࡓࠋ
ࡇࡢ⤖ᯝࡼࡾࠊࡇࢀࡽࡢṧᇶࡣࠊศᏊෆ㒊࡛ᙉᅛ࡞Ỉ⣲⤖ྜࢆᙧᡂࡋ࡚࠾ࡾࠊRxRࡢ
ᬯ≧ែࡢᵓ㐀⥔ᣢ࡟㔜せ࡞ṧᇶ࡛࠶ࡿࡇ
࡜ࡀ⪃࠼ࡽࢀࡓࠋ୍᪉ࠊࣉࣟࢺࣥཷᐜᇶࡢ
D85ࡸࣉࣟࢺࣥᨺฟᇶࡢE187⏤᮶ࡢࢩࢢࢼࣝࡣほ ࡉࢀ࡚࠾ࡽࡎࠊᙉᅛ࡞Ỉ⣲⤖ྜࢆᙧᡂࡋ࡚࠸࡞࠸≧ែ࡛࠶ࡿࠊࡲࡓࡣ⬺ࣉࣟࢺࣥ໬≧ែ࡛࠶ࡿࡇ࡜ࡀ⪃࠼ࡽࢀࡓࠋ

Fig. 2 Schematic of hydrogen-bonding networks aroundretinal (A) as inferred from the crystal structure of RxR(B, PDB:6KFQ)

2㸬H/D ஺᥮ᐇ㦂࡟ࡼࡿᬯ≧ែ࡟࠾࠸࡚ほ ࡉࢀࡓ஺᥮ᛶỈ⣲ࡢ࢟ࣕࣛࢡࢱࣜࢮ࣮ࢩࣙࣥ
ほࡉࢀࡓ஺᥮ᛶỈ⣲ࡢ࢟ࣕࣛࢡࢱࣜ

ࢮ࣮ࢩࣙࣥࢆ┠ⓗ࡜ࡋࠊH/D ஺᥮ᐇ㦂ࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊY49ࠊD108 ⏤᮶ࡢࢩࢢࢼࣝ࡜ Y178 ⏤᮶ࡢࢩࢢࢼࣝ࡟ࡣ H/D
஺᥮㏿ᗘ࡟㐪࠸ࡀ࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓ(Fig. 3)ࠋY49ࠊD108 ⏤᮶ࡢࢩࢢࢼࣝࡣࠊ
ヨᩱࢆ㔜Ỉ⨨᥮ࡋࡓ┤ᚋࡢࢫ࣌ࢡࢺ࡛ࣝ
ほࡉࢀ࡞࠿ࡗࡓࡇ࡜࠿ࡽࠊ10-3 sec-1 ௨ୖࡢ H/D ஺᥮㏿ᗘ࡛࠶ࡿࡇ࡜ࡀ᥎ᐃࡉ

Fig. 3 H/D exchange experiment on RxR.
15

N-filtered ¹H-NMR spectra of [15N] RxR in H2O buffer(A) and after 7 hours in D2O buffer (B).

ࢀࡿ୍᪉࡛ࠊY178 ⏤᮶ࡢࢩࢢࢼࣝࡢ H/D ஺᥮㏿ᗘࡣࠊ⤒᫬ኚ໬ࡢゎᯒ⤖ᯝࡼࡾ 4.5×10-6 sec-1 ࡛－ 169 －

࠶ࡗࡓࠋ୍᪉࡛ࠊCLEANEX-PMᐃࢆᐇ᪋ࡋࡓ࡜ࡇࢁࠊࣂࣝࢡỈ࠿ࡽࡇࢀࡽࡢ஺᥮ᛶỈ⣲࡬ࡢ☢

໬⛣⾜ࡣ᳨ฟࡉࢀ࡞࠿ࡗࡓࡇ࡜࠿ࡽࠊỈศᏊ࡜ࡢ஺᥮㏿ᗘࡣ < 10-1 sec-1 ࡛࠶ࡿࡇ࡜ࡶ᥎ᐃࡉࢀࡓ
2ࠋศᏊෆ࡛ᙉᅛ࡞Ỉ⣲⤖ྜࢆᙧᡂࡋ࡚࠸ࡿ≧ែ࡛ࡶࠊH/D ஺᥮཯ᛂࡀ㉳ࡁࡿࡇ࡜ࡀ♧ࡉࢀࠊྠࡌ

Ỉ⣲⤖ྜࢿࢵࢺ࣮࣡ࢡ࡟Ꮡᅾࡍࡿṧᇶ࡛ࡶ H/D ஺᥮㏿ᗘ࡟㐪࠸ࡀ࠶ࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓࠋ
3㸬Ỉ⣲⤖ྜࢿࢵࢺ࣮࣡ࢡ࡟㛵୚ࡍࡿ࢔࣑ࣀ㓟⨨᥮యࡢ NMR

ᐃ࡜㍺㏦άᛶホ౯ࣞࢳࢼ࣮ࣝ㏆ഐࡢỈ⣲⤖ྜࢿࢵࢺ࣮࣡ࢡࡢ
᰾࡜࡞ࡿṧᇶ࡛࠶ࡾࠊࣉࣟࢺࣥ㍺㏦࡟┤᥋㛵୚ࡍࡿ D74 ࡜ D205 ࡢ࢔࣑ࣀ㓟⨨᥮యࡢ NMR
ᐃࢆ⾜࠺࡜ࠊY49ࠊY178 ⏤᮶ࡢࢩࢢࢼࣝࡀ
ᾘኻࡍࡿࡇ࡜ࡀุ᫂ࡋࡓ(Fig. 4)ࠋD74 ࡢ࢔࣑ࣀ㓟⨨᥮య D74N RxR ࡣࣉࣟࢺࣥ㍺㏦άᛶࢆ
᭷ࡋ࡚࠾ࡽࡎࠊD205N RxR ࡢࣉࣟࢺࣥ㍺㏦ά
ᛶࡣ㔝⏕ᆺࡢ 4 ศࡢ 1 ௨ୗ࡛࠶ࡿࡇ࡜ࡀሗ࿌
ࡉࢀ࡚࠸ࡿ 4ࠋᮏᐇ㦂⤖ᯝࡼࡾࠊ஺᥮ᛶỈ⣲ࡀ᳨ฟࡉࢀࡓ Y49 ࠾ࡼࡧ Y178 ࡣࠊ᥎ᐃࡉࢀࡿ
Ỉ⣲⤖ྜࢿࢵࢺ࣮࣡ࢡෆ࡛ D74ࠊD205 ࡜┦஫Fig. 4 15N-filtered ¹H-NMR spectra of [15N] RxR(A) and the counterion mutants; D74N RxR (B) andD205N RxR (C).

స⏝ࡋࠊᶵ⬟Ⓨ⌧ࢆ⥔ᣢࡍࡿ㔜せ࡞ᙺ๭ࢆ᭷ࡋ࡚࠸ࡿ࡜᥎ᐃࡉࢀࡓࠋ
4㸬ග↷ᑕ NMR

ᐃ 5 ࡟ࡼࡿග཯ᛂࢧ࢖ࢡࣝ୰㛫య⏤᮶ࢩࢢࢼࣝࡢ᳨ฟ

RxRࡢࣞࢳࢼ࣮ࣝࡢ྾཰ᴟ኱㏆ഐࡢἼ㛗525nmࡢගࢆ↷ᑕࡋࡓ15N-filtered 1H-NMR ᐃࢆ⾜ࡗࡓ࡜ࡇࢁࠊ3ࡘࡢ஺᥮ᛶỈ⣲ࢩࢢࢼࣝࡢᙉᗘ
ࡀపୗࡋࠊ᪂ࡓ࡞ࢩࢢࢼࣝࡀほ ࡉࢀࡓࠋග
↷ᑕᚋࡢᚅᶵ᫬㛫 (d21) ࢆኚ໬ࡉࡏࡓ᫬㛫ศゎィ ࡢ⤖ᯝࠊග↷ᑕNMR࡛᪂ࡓ࡟ほ ࡋࡓࢩࢢࢼࣝࡣ20~30 msࡢᑑ࿨ࡢ୰㛫య⏤᮶࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓ (Fig. 5A)ࠋග཯ᛂࢧ࢖ࢡࣝ
ゎᯒ⤖ᯝ࡜⪃࠼ྜࢃࡏࡿ࡜ࠊග↷ᑕ ᐃ࡟ࡼࡾ᳨ฟࡉࢀ࡚࠸ࡿ≧ែࡣࠊග཯ᛂ࡟࠾ࡅࡿᚋ
ᮇ୰㛫య࡛࠶ࡿ࡜⪃࠼ࡽࢀࡓࠋ
ග↷ᑕ NMR ᐃ࡟ࡼࡗ࡚ほ ࡉࢀࡓ᪂ࡓ࡞
ࢩࢢࢼࣝࡢ⏤᮶ࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵࠊΰྜᮇ
(50 ms)࡟ගࢆ↷ᑕࡋࡓ 15N-filtered 1H-1H EXSY
(SC-NMR) ᐃࢆ⾜ࡗࡓ (Fig. 5B)ࠋࡑࡢ⤖ᯝࠊ

Fig. 5 (A) Time-resolved ¹H-NMR spectra of [15N]

Y49 ⏤᮶ࡢࢩࢢࢼࣝࡣ 0.4 ppmࠊY178 ⏤᮶ࡢࢩRxR (gray; d21= 1, 10, 16, 24, 36 msec,

ࢢࢼࣝࡣ 1.0 ppm ࡢ㧗☢ሙࢩࣇࢺࡋࡓࢩࢢࢼࣝ

black; d21 = 100 ms).
15࡜┦㛵ࣆ࣮ࢡࢆ♧ࡋࠊᚋᮇ୰㛫య≧ែ࡛ࡶỈ⣲(B) N-filtered ¹H-¹H EXSY (SC-NMR) spectrum⤖ྜࡀ⥔ᣢࡉࢀ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡑࡢ

of [15N] RxR with the light irradiation during the୍᪉࡛ࠊD108 ⏤᮶ࡢࢩࢢࢼࣝࡣほmixing time.

ࡉࢀࡎࠊD108 ࡀᙧᡂࡋ࡚࠸ࡿỈ⣲⤖ྜࡣ୙Ᏻᐃ࡞≧ែ࡟࡞ࡗ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡓࠋ

－ 170 －

5㸬ග↷ᑕ NMRᐃ࡟࠾࠸࡚ほ ࡉࢀࡓప☢ሙࢩࣇࢺࡋࡓࢩࢢࢼࣝࡢゎᯒග↷ᑕୗ࡛ 1H-NMRᐃࢆ⾜ࡗࡓ࡜ࡇࢁࠊ

12.7 ppm ௜㏆࡟ࠊ15N-filtered¹H-NMR ࡛ࡣほࡉࢀ࡞࠿ࡗࡓ NH ⏤᮶ࢩࢢࢼࣝࡀほ ࡉࢀ
ࡓ (Fig. 6 A)ࠋప☢ሙࢩࣇࢺࡋࡓ NH ⏤᮶ࡢࢩࢢࢼࣝࡢྠᐃ࡟ྥࡅ࡚ග↷ᑕୗ࡛ࡢ 1H-1H
EXSY (SC-NMR)

ᐃ (Fig. 6 B)ࢆ⾜ࡗࡓ⤖ᯝࠊ᳨ฟࡉࢀࡓ NH ⏤᮶ࡢࢩࢢࢼࣝࡣ Trp ഃ㙐⏤᮶࡛࠶ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ࢔࣑ࣀ㓟ṧᇶ⨨᥮య࡟ࡼࡾ Trp ഃ㙐⏤᮶ࢩࢢࢼࣝࡢᖐᒓ
ࢆ⾜ࡗࡓ⤖ᯝࠊretinal ㏆ഐ࡟Ꮡᅾࡍࡿ W75 ࡢഃ㙐⏤᮶ࢩࢢࢼࣝࡀᚋᮇ୰㛫య࡟࠾࠸࡚ 3.0
ppm ࡢ㢧ⴭ࡞ప☢ሙࢩࣇࢺࢆࡋ࡚࠸ࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋRxR ࡜┦ྠᛶࡢ㧗࠸ bacteriorhodopsin (BR)ࡢග཯ᛂ୰㛫యࡢ᫬㛫ศゎ⤖ᬗᵓ㐀࡛ࡣࠊᬯ≧ែ࡟ẚ࡭ࠊᚋᮇ୰㛫య࡛ࡣࠊBR W86 (RxR
W75)ࡢഃ㙐࢖ࣥࢻ࣮ࣝ❅⣲ࡀࠊBR D216 (RxR
D205)ഃ㙐࡟᥋㏆ࡍࡿࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠸ࡿ
6

ࠋRxR ࡢග↷ᑕ NMR

ᐃ࡛ほ ࡉࢀࡓ W75

ࡢప☢ሙࢩࣇࢺࡣࠊᚋᮇ୰㛫య≧ែ࡟࠾࠸࡚

Fig. 6 (A) 1H-NMR spectra of the dark-adapted state(black) and the light-adapted state (gray). The
resonance originating from Trp indole NH is
surrounded by dotted-line box. (B) ¹H-¹H EXSY
(SC-NMR) spectrum of [15N] RxR with the lightirradiation period prior to the NOESY pulse scheme.

W75 ࡜ D205 ࡜ࡢ㊥㞳ࡀᬯ≧ែࡼࡾࡶ㏆࡙ࡁࠊỈ⣲⤖ྜࡀᙉᅛ࡟࡞ࡗࡓࡇ࡜࡟㉳ᅉࡍࡿ࡜᥎ᐃࡉ
ࢀࡓࠋW75 ࡢ࢔࣑ࣀ㓟⨨᥮యࡢࣇࣛࢵࢩࣗࣇ࢛ࢺࣜࢩࢫゎᯒ࡛ࡣࠊ㔝⏕ᆺ࡜ẚ࡭࡚ᚋᮇ୰㛫యࡢ᫬ᐃᩘࡀ㛗ࡃ࡞ࡿࡇ࡜ࡀ♧ࡉࢀ࡚࠾ࡾࠊW75 ࡜ D205 ࡢ┦஫స⏝ࡣᚋᮇ୰㛫యᵓ㐀ᙧᡂ࡟㔜せ࡞ᙺ๭ࢆᯝࡓࡍࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
[Conclusion] ᮏ◊✲࡛ࡣࠊ㏻ᖖࠊほࡀᅔ㞴࡜⪃࠼ࡽࢀ࡚࠸ࡿ㓟⣲ཎᏊ࡟⤖ྜࡋࡓ஺᥮ᛶỈ⣲ࡀࠊࣉࣟࢺࣥ

࣏ࣥࣉࣟࢻࣉࢩࣥࡢάᛶ㒊఩㏆ഐ࡛ほ ࡉࢀ࡚࠾ࡾࠊࡑࢀࡽࡀᶵ⬟ୖ㔜せ࡞Ỉ⣲⤖ྜࢿࢵࢺ࣮࣡
ࢡᙧᡂ࡟ᐤ୚ࡋ࡚࠸ࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓࠋࡉࡽ࡟ࠊᬯ≧ែࠊග཯ᛂ୰㛫య࡟࠾ࡅࡿࡇࢀࡽ஺᥮
ᛶỈ⣲⏤᮶ࢩࢢࢼࣝࡢ┦㛵ࡀ᫂ࡽ࠿࡟࡞ࡿ࡜࡜ࡶ࡟ࠊάᛶ㒊఩㏆ഐW75ࡢഃ㙐NHࡣග཯ᛂ୰㛫య࡟࠾࠸࡚㢧ⴭ࡞ప☢ሙࢩࣇࢺࡋࠊᙉᅛ࡞Ỉ⣲⤖ྜ࡟ᐤ୚ࡍࡿࡇ࡜ࡀ᥎ᐃࡉࢀࡓࠋࡇࢀࡽࠊY49ࠊ
Y178ࠊW75࡜࠸ࡗࡓṧᇶࡣࠊ௚ࡢࣉࣟࢺ࣏ࣥࣥࣉࣟࢻࣉࢩࣥ࡟࠾ࡅࡿಖᏑᛶࡀ㧗ࡃࠊࡇࢀࡽࡢṧᇶ࡟㛵ࡍࡿ▱ぢࡣᬑ㐢ᛶࡀ㧗࠸ࡶࡢ࡛࠶ࡿ࡜⪃࠼࡚࠸ࡿࠋ
[References](1) Sigala PA Tsuchida MA, Herschlag D. (2009) PNAS. 106, 23.
(2) Baturin SJ, Okon M and Mclntosh LP. (2011) J Biomol NMR. 51, 379.
(3) Kanehara K, Yoshizawa S, Tsukamoto T and Sudo Y. (2017) Sci. Rep. 7, 44427.
(4) Kojima K, Ueta T, Noji T, Saito K, Kanehara K, Yoshizama S, Ishitaka H and Sudo Y. (2020) Sci. Rep. 10, 282.
(5) Nagashima T, Ueda K, Nishimura C and Yamazaki T. (2015) Anal Chem. 87, 22.
(6) Borshchevskiy V et al. (2022) Nat Struct Mol. Biol. 29, 5.

－ 171 －

P19

CO2ࡢࢲ࢖ࢼ࣑ࢡࢫࢆ㏻ࡌࡓከᏍᛶ㓄఩㧗ศᏊࡢᵓ㐀㌿⛣㐣⛬ࡢゎᯒ‫ۑ‬᭮฼ᝳᜨ1㸪ᰩཎᣅஓ1㸪㞵᳃⩧ᝅ2㸪㔜⏣Ὀᏹ2㸪஭⏣᭸ᬛ1㸪Ỉ㔝ඖ༤1,2
1 㔠ἑ኱Ꮫ኱Ꮫ㝔⮬↛⛉Ꮫ◊✲⛉
2 㔠ἑ኱Ꮫࢼࣀ࣐ࢸࣜ࢔ࣝ◊✲ᡤ

Study of structural transition process of a porous coordination polymer throughobservation of adsorbed CO2 dynamics‫ۑ‬Yue Souri1, Takuya Kurihara1, Yasuhiro Shigeta2, Syogo Amemori2, Tomonori Ida1, Motohiro Mizuno1,2
1 Graduate School of Natural Science and Technology, Kanazawa University
2 Nanomaterials Research Institute, Kanazawa University
Porous coordination polymers (PCPs) have been studied as gas-adsorption materials. Flexible PCPs
frequently show adsorption-induced pore-expansion behavior called “gate opening”. The gate-opening
phenomenon has been attracted attention as a useful property for gas separation because of its gas-selective
feature. However, the mechanism of guest-induced structural transition in gate opening has not been
sufficiently understood. In this study, we investigated gate-opening mechanism of a PCP through dynamics
of adsorbed CO2 by solid-state 13C NMR. Analyses of 13C chemical shift anisotropy (CSA) and T1 relaxation
times indicate that the structural transition of the PCP gradually progresses from crystallite surface to corewith increasing CO2 pressure.
࠙ᗎㄽࠚከᏍᛶ㓄఩㧗ศᏊ(PCP)ࡣࠊ㔠ᒓ࢖࢜ࣥ࡜㓄఩Ꮚ࠿ࡽᡂࡿከᏍᛶ㔠ᒓ㘒య࡛࠶ࡾࠊ࢞ࢫ྾╔ᮦᩱ࡜ࡋ࡚◊✲ࡉࢀ࡚࠸ࡿࠋ㓄఩⤖ྜ࡞࡝ࡢẚ㍑ⓗᙅ࠸┦஫స⏝࠿ࡽ࡞ࡿᰂ㌾࡞㦵᱁ࢆᣢࡘࡓࡵࠊ୍㒊ࡢPCPࡣࢤ࣮ࢺ࣮࢜ࣉࣥ࡜࿧ࡤࢀࡿࠊ࠶ࡿ࢞ࢫᅽ࡛⣽Ꮝᚄࡢᣑ኱ࢆక
࠺⤖ᬗᵓ㐀㌿⛣ࡀ⏕ࡌࠊ࢞ࢫ྾╔㔞ࡀᛴቑࡍࡿ⌧㇟ࢆ♧ࡍࠋ྾╔ࡍࡿศᏊ࡟ࡼࡗ࡚ࢤ࣮ࢺ࣮࢜ࣉࣥࡢ㉳ࡁࡿᅽຊࡀ␗࡞ࡿࡓࡵࠊ࢞ࢫศ㞳࡟᭷⏝࡞≉ᛶ࡜ࡋ࡚ὀ┠ࡉࢀ࡚࠸ࡿࠋࢤ࣮ࢺ࣮࢜ࣉ࡛ࣥࡣ࢞ࢫࡀPCP࡜┦஫స⏝ࡍࡿࡇ࡜࡛ࠊᵓ㐀ࢆᙧᡂࡍࡿ㓄఩Ꮚ㛫┦஫స⏝ࡢᵝᏊࡀኚ໬ࡋࠊᵓ㐀㌿⛣ࡀ⏕ࡌࡿ[1]ࠋ୍᪉࡛ࠊ࡝ࡢࡼ࠺࡟࢞ࢫࡀPCP࡜┦஫స⏝ࡋ࡚ᵓ㐀㌿⛣ࡀ㐍⾜ࡍࡿࡢ࠿ࠊࡑࡢ㐣⛬ࡣ᫂ࡽ࠿࡛ࡣ࡞࠸ࠋᮏ◊✲࡛ࡣࠊCO2 ࡟ᑐࡋ࡚ࢤ࣮ࢺ࣮࢜ࣉࣥࢆ♧ࡍCID-5([Zn(4,4’-bipyridine)(5-NO2-isophtalate)]n, Fig. 1)[2]࡟ᑐࡋࠊCO2㞺ᅖẼୗ࡟࠾ࡅࡿᅛయNMR ᐃࢆ⾜࠸ࠊ྾╔ࡍࡿCO2ࡢࢲ࢖ࢼ࣑ࢡࢫࡢゎᯒࢆ㏻ࡌࡓᵓ㐀㌿⛣ࡢ࣓࢝ࢽࢬ࣒ࡢゎ᫂ࢆヨࡳࡓࠋ࠙ᐇ㦂ࠚCIDࡣ᪤ሗ࡟ᚑ࠸ྜᡂࡋࡓ[2]ࠋCO2㞺ᅖẼୗ⢊ᮎXRD ᐃ(Ἴ㛗0.7999 Ⴒ)ࡣSPring-8࡟࡚⾜ࡗࡓࠋᅛయNMR ᐃࡣ7 Tࡢ☢ሙ࡟࠾࠸࡚MAS㏿ᗘࢆ4 kHz࡜ࡋ࡚ᐇ᪋ࡋࡓࠋOࣜࣥࢢࡢ௜࠸ࡓࢫ
ࢡ࣮ࣜࣗᘧ࢟ࣕࢵࣉࢆഛ࠼ࡓ⮬సヨᩱ⟶ࢆ࢞ࢫᑟධ⏝ࣛ࢖ࣥ୰࡛ࡩࡓࢆࡍࡿࡇ࡜࡛[3]ࠊ13CO2 (13C࢞ࢫ㞺ᅖẼୗᅛయNMR㸪ከᏍᛶ㓄఩㧗ศᏊ㸪ࢤ࣮ࢺ࣮࢜ࣉࣥ
‫࠼ࡺࡾ࠺ࡑۑ‬㸪ࡃࡾࡣࡽࡓࡃࡸ㸪ࡋࡆࡓࡸࡍࡦࢁ㸪࠶ࡵࡶࡾࡋࡻ࠺ࡈ㸪࠸ࡔ࡜ࡶࡢࡾ㸪ࡳࡎࡢࡶ࡜ࡦࢁ

－ 172 －

99%)ୗ࡟࠾ࡅࡿ13C ᐃࢆ⾜ࡗࡓࠋCO2྾╔➼ ⥺(Fig. 2a)ࡼࡾ࢞ࢫᅽࡣ0 MPaࠊࢤ࣮ࢺ࣮࢜ࣉࣥ┤๓࣭᭱୰࣭┤ᚋࡢ0.14, 0.29, 0.44 MPaࠊ࠾ࡼࡧࠊ྾╔㔞ࡀ㣬࿴ࡋ࡚࠸ࡿ0.79 MPaࡢ5Ⅼ࡟タᐃࡋࡓࠋ࠙⤖ᯝ࣭⪃ᐹࠚCO2㞺ᅖẼୗXRDᐃࡢ⤖ᯝ

ࢆFig. 2b࡟♧ࡍࠋ0.300 MPaࢆቃ࡟XRDࣃࢱ࣮ࣥࡀኚ໬ࡋࡓࡇ࡜࠿ࡽࠊ྾╔➼ ⥺࡟♧ࡉࢀ
ࡿ㏻ࡾ0.3 MPa௜㏆࡟࠾࠸࡚ᵓ㐀㌿⛣ࡀ㉳ࡁ࡚࠸ࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋ㌿⛣ࡢ㐍⾜㏵୰࡟࠶ࡓࡿ0.300 MPa࡛ࡣࠊ㌿⛣๓ࡢclosedᵓ㐀࡜㌿⛣ᚋࡢcopenᵓ㐀ࡢࣃࢱ࣮ࣥࡀΰᅾࡋࠊ2┦ࡀΰᅾࡋ࡚࠸ࡿࡇ࡜ࡀㄞࡳྲྀࢀࡿࠋ
13C 1-pulse MASᐃ࡟ࡼࡾࠊ྾╔ࡋࡓCO2ࡢ㐠ື≧ែࢆゎᯒࡋࡓࠋ13Cࢫ࣌ࢡࢺࣝ࡟ࡣ඲ᅽຊୗ࡛

ࢫࣆࢽࣥࢢࢧ࢖ࢻࣂࣥࢻಙྕࡀほ ࡉࢀࡓࠋ(Fig. 3 ) ࡇࢀࡣCO2ࡀCID࡜┦஫స⏝ࠊࡘࡲࡾࡣ྾╔ࡋ㐠ືࡀ␗᪉ⓗ࡟ไ㝈ࡉࢀ࡚࠸ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋCO2ࡢ྾╔≧ែࢆㄪ࡭ࡿࡓࡵ࡟ࠊࢧ࢖ࢻࣂࣥ
ࢻಙྕ࡟ᑐࡋ໬Ꮫࢩࣇࢺ␗᪉ᛶ(CSA)ࡢゎᯒࢆ⾜ࡗࡓࠋ(Table 1) ྛᅽຊୗ࡛ぢ࠿ࡅࡢCSAࡢ್࡟኱ࡁ࡞㐪࠸ࡣ࡞࠿ࡗࡓࡇ࡜࠿ࡽࠊ⣽Ꮝࢆᣢࡘopenᵓ㐀࡜⣽Ꮝࡀ㛢ࡌࡓclosedᵓ㐀(0.14 MPa)࡛CO2
ࡢ྾╔≧ែࡣ㏆࠸ࡇ࡜ࡀࢃ࠿ࡿࠋࡘࡲࡾࠊᵓ㐀㌿⛣๓࡛࠶ࡿ0.14 MPa࡟࠾࠸࡚ࡶCO2ࡀ⣽Ꮝෆ࡟྾╔ࡋ࡚࠸ࡿ࡜♧၀ࡉࢀࡿࠋXRDࣃࢱ࣮࡛ࣥࡣ0.14 MPaࡣclosedᵓ㐀࡛࠶ࡿࡀࠊXRD࡛ࡣぢ࠼࡞࠸⤖ᬗ⢏Ꮚࡢ⾲㠃௜㏆ࡢࡳࡀopenᵓ㐀࡟㌿⛣ࡋ࡚࠾ࡾࠊࡑࡢ⣽Ꮝ࡟CO2ࡀ྾╔ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ
ḟ࡟ࠊ0.300 MPaࡢopenᵓ㐀࡜closedᵓ㐀ࡢ2┦ࡀΰᅾࡋ࡚࠸ࡿ≧ែ࡟ࡘ࠸࡚ࠊCO2ࡢ13C T1⦆࿴᫬㛫ࡼࡾゎᯒࢆ⾜ࡗࡓࠋclosedᵓ㐀࡜openᵓ㐀࡟㌿⛣ࡋࡓ2✀㢮ࡢ⤖ᬗ⢏Ꮚࡀΰᅾࡋ࡚࠸
ࡿ≧ែࢆ௬ᐃࡋclosedᵓ㐀࡛࠶ࡿ0.14 MPaࡢT1 ࡜openᵓ㐀࡛࠶ࡿ0.79 MPaࡢT1 ࡢ2ࡘࡢ್ࢆ⏝࠸ࡓdouble exp࡛ࡣࠊ0.29 MPa࡟࠾ࡅࡿT1
⦆࿴ࡢᵝᏊࢆ෌⌧࡛ࡁ࡞࠿ࡗࡓࠋࡑࡢࡓࡵࠊ
1ࡘࡢ⤖ᬗ⢏Ꮚෆ࡟㌿⛣ࡋࡓ㒊ศ(openᵓ㐀)࡜㌿⛣ࡋ࡚࠸࡞࠸㒊ศ(closedᵓ㐀)ࡀඹᏑࡋ
ࡓ≧ែ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋྛᅽຊࡢT1 ࡣsingle exp᭤⥺࡛ゎᯒ࡛ࡁࠊࡲࡓᅽຊቑຍ࡟క
࠸㛗ࡃ࡞ࡗࡓࠋࡇࢀࡣࠊẼయࡢCO2࡜྾╔ࡋࡓ
CO2ࡢ㛫࡛஺᥮ࡀ㉳ࡁT1ࡀᖹᆒ໬ࡉࢀ࡚࠸ࡿ
ࡓࡵ࡛࠶ࡾࠊ྾╔ࡋࡓCO2ࡢ๭ྜࡀቑ࠼ࡿ࡟
ࡘࢀ࡚T1ࡀ㛗ࡃ࡞ࡗࡓ࡜⪃࠼ࡽࢀࡿࠋ௨ୖࡼ
ࡾࠊCID࡟࠾࠸࡚ᵓ㐀㌿⛣ࡣ࢞ࢫᅽࡢቑຍ࡜
࡜ࡶ࡟ࠊ⤖ᬗ⾲㠃࠿ࡽ୰ᚰ㒊࡬ྥ࠿࠸ᚎࠎ࡟
㐍⾜ࡋ࡚࠸ࡃࡇ࡜ࡀ♧ࡉࢀࡓࠋ
References(1) H. Yang et al., ACS Cent. Sci. 2018, 4, 1194í1200.
(2) S. Horike et al., Chem. Sci. 2012, 3, 116-120.
(3) T. Kurihara et al., J. Phys. Chem. Lett. 2022, 13, 7023-7028－ 173 －

P20Y

㓟⣲ྠ఩య࠾ࡼࡧ㧗ឤᗘᅛయ2105࡟ࡼࡿ▼Ⅳࡢ
㓟໬཯ᛂᶵᵓゎᯒ‫཭⏿ۑ‬㍤㸪ዟୗ៞Ꮚ㧗ᶫ㈗ᩥ㔠ᶫᗣ஧㰻⸨ බඣ๎Ọ ⾜ᗤ
1᪥ᮏ〇㕲ᰴᘧ఍♫ ඛ➃ᢏ⾡◊✲ᡤ
2᪥㕲ࢸࢡࣀࣟࢪ࣮ᰴᘧ఍♫3᪥㕲⥲◊ᰴᘧ఍♫4ྡྂᒇ኱Ꮫ ໬ᏛᕤᏛࢩࢫࢸ࣒ᑓᨷ

Oxidization mechanism analysis using isotope oxygen gas and high sensitivity solid state
17O NMR spectra for coal.
żYuki Hata1,4, Keiko Okushita1, Takafumi Takahashi1, Koji Kanehashi2, Koji Saito3, Koyo Norinaga4
1Advanced Technology Research Laboratories, Nippon Steel Corporation

2 Nippon Steel Technology Co., Ltd.
3 Nippon Steel Research Institute Corporation
4 Department of Chemical Systems Engineering, Graduate School of Engineering, Nagoya University

For direct observation of oxygen functional groups generated during oxidation reaction and analysis of theoxidation mechanism, coal was treated at 40 – 150 degree C under 17O2 atmosphere. Solid state 17O MAS
NMR spectra of the oxidized coal were acquired by using oldfield echo pulse sequence. Since the 17O MAS
NMR spectrum acquired by single pulse sequence suffered from distortion caused by ringing phenomenon,
the oldfield echo pulse sequence was used to eliminate the spectral distortion. As a result, two kinds of oxygen
functional groups generated by oxidation were observed. Based on the quantitative analysis of 17O MAS
NMR spectra, it was found that the amount of oxygen functional groups increased with an increase ofoxidation temperature. Furthermore, pjMATPASS sequence revealed aldehyde group generated in oxidized
coal by eliminating the spinning side band (ssb) interference from 17O MAS NMR spectra.
[1] ⥴ゝ
┬CO2᤼ฟࡸࢥࢫࢺ➇தຊྥୖ࡟ྥࡅ࡚ࠊ௒ᚋࠊపရ఩ࡢ▼Ⅳࡸࣂ࢖࣐࢜ࢫࡢά⏝ࡀ୍ᒙồࡵࡽࢀࡿࠋ
୍᪉ࠊపရ఩ࡢ▼Ⅳࡸࣂ࢖࣐࢜ࢫࡣ⮬↛Ⓨ⇕ࡋ᫆࠸ᛶ㉁ࡀ࠶ࡾࠊࡇࡢⓎ⇕࡟㉳ᅉࡋࡓ኱つᶍ࡞ⅆ⅏ࡸ஦ᨾࡀྂࡃ࠿ࡽ▱ࡽࢀ࡚࠾ࡾ1)ࠊ༑ศ࡞ᑐ⟇ࡀᚲせ࡛࠶ࡿࠋ⮬↛Ⓨ⇕ࡢᢚไἲ☜❧ࡸᏳ඲࡞⟶⌮ᢏ⾡ᵓ⠏࡟ࡣ⮬↛Ⓨ⇕⌧㇟ࢆ໬Ꮫⓗ࡟⌮ゎࡍࡿᚲせࡀ࠶ࡾࠊࡑࡢࡓࡵ࡟ࡣࠊ㓟໬཯ᛂ࡟ࡼࡿ▼ⅣࡢศᏊᵓ㐀ኚ໬࡟㛵ࡍࡿ▱ぢࡀᚲせ࡛࠶ࡿࠋWangࡽ2) ࡣFT-IRࡸXPSࢆ⏝࠸࡚ࠊ㓟໬཯ᛂ᫬ࡢ㓟⣲ᐁ⬟ᇶ⏕ᡂࢆぢฟࡋࡓࠋࡲࡓࠊෆ⏣ࡽ3) ࡣࠊ18O2 ⃰⦰࢞ࢫ㞺ᅖẼୗ࡛▼Ⅳࢆ㓟໬ࡉࡏࡓ㝿ࠊⓎ⏕ࡋࡓ୺࡞࢞ࢫࡣ16Oࢆ
ྵࡴCO ࠾ࡼࡧCO2࡛࠶ࡗࡓࡇ࡜࠿ࡽࠊ㞺ᅖẼࡢ 18Oࡣ▼Ⅳෆ㒊࡟ᅛᐃࡉࢀࡿࡇ࡜ࢆ♧ࡋࡓࠋࡋ࠿ࡋ࡞
ࡀࡽࠊࡇࡢᅛᐃࡉࢀࡓ㓟⣲ࡀࠊ▼Ⅳࡢ㓟⣲ᐁ⬟ᇶ࡟ྲྀࡾ㎸ࡲࢀࡓ᫂☜࡞ドᣐࡣᚓࡽࢀ࡚࠸࡞࠸ࠋᮏ◊✲࡛ࡣࠊᅛయNMRἲ࡟ࡼࡾ▼Ⅳ୰ࡢ㓟⣲ࢆ┤᥋ほࡍࡿࡇ࡜࡛ࠊ㞺ᅖẼ㓟⣲ࡀྲྀࡾ㎸ࡲࢀࡿ໬Ꮫᵓ㐀ࢆゎ᫂ࡍࡿ࡜ඹ࡟ࠊࡑࡢ᝟ሗࢆᇶ࡟㓟໬཯ᛂᶵᵓࢆ᳨ウࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋࡓࠋ㏻ᖖࠊኳ↛▼Ⅳ࡟Ꮡᅾࡍࡿ㓟⣲ᐁ⬟ᇶࡣṤ࡝16O࡛࠶ࡾࠊNMR࡛ほ࡛ࡣ17Oࡢ

ྍ⬟࡞17Oࡣࠊഹ࠿0.038%࡟㐣ࡂ࡞࠸ࠋࡑࡢࡓࡵࠊኳ↛▼Ⅳᐃឤᗘࡀ୙㊊ࡋ㓟⣲ᐁ⬟ᇶࡢほࡣ୙ྍ⬟࡛࠶ࡿࠋࡑࡇ࡛ࠊ17Oࢆ▼Ⅳ୰࡟⃰⦰ࡍࡿࡇ࡜ࢆ

╔᝿ࡋࠊ17O2 㞺ᅖẼୗ࡛㓟໬Ⅳࢆㄪ〇ࡋࡓࠋ

2㸪㧗ឤᗘ㸪&U\R‫ࡁ࠺ࡺࡓࡣۑ‬㸪࠾ࡃࡋࡓࡅ࠸ࡇ㸪ࡓ࠿ࡣࡋࡓ࠿ࡩࡳ㸪࠿ࡡࡣࡋࡇ࠺ࡌ㸪ࡉ࠸࡜࠺ࡇ࠺ࡌ㸪ࡢࡾ࡞ࡀࡇ࠺ࡼ࠺

－ 174 －

䛣䜜䜎䛷䛻䚸୍㒊䜢䝷䝧䝹໬䛧䛯䝍䞁䝟䜽㉁ 4) 䜔䝇䝷䜾 5) 䛺䛹䛾 17O
NMR 䝇䝨䜽䝖䝹17ᐃ౛䛿䛒䜛䛜䚸▼Ⅳ࡬ࡢ㐺⏝౛ࡣ↓࠸ࠋࡲࡓࠊ

O ࡣඹ㬆࿘Ἴᩘࡀప࠸ࡓࡵࠊNMR ࢫ࣌ࢡࢺࣝ

ᐃ᫬࡟ࡣࠊࣜࣥࢠࣥࢢ࡟ࡼࡗ࡚ࢫ࣌ࢡࢺࣝࡢ࠺ࡡࡾࡀ⏕ࡌࡸࡍࡃࠊ ᐃࡀᅔ㞴࡞᰾✀࡛࠶ࡿࠋᮏ◊✲࡛ࡣࠊ17O NMRᐃ᫬ࡢࣃࣝࢫࢩ

࣮ࢣࣥࢫࢆᕤኵࡋࠊࢫ࣌ࢡࢺࣝࡢ࠺ࡡࡾࡢᢚไࢆヨࡳࡓࠋ[2] ᐇ㦂
⮬↛Ⓨ⇕ᛶࡀ㧗࠸▼Ⅳࢆ 150 Pm ௨ୗ࡟⢊○ࡋࠊ80 ºC ࡛ 12᫬㛫┿✵஝⇱ࡉࡏࠊ㓟໬๓ࡢ▼Ⅳヨᩱࢆᚓࡓࠋࡉࡽ࡟ࠊ▼Ⅳ
ヨᩱ࡜ 17O2 ࢆ཯ᛂࡉࡏࡿࡓࡵ࡟స〇ࡋࡓᑓ⏝ࡢ࢞ࣛࢫ〇ࡢࢭࣝ࡟ࠊ㓟໬๓▼Ⅳ⢊ᮎヨᩱ 0.5 g ࡜ 1.0 atm ࡢ 17O ࢞ࢫࢆ඘ሸ

Fig. 1 17O MAS NMR spectra of oxidized coalࡋࡓࠋḟ࡟ࠊ▼Ⅳヨᩱ࡜ 17O ࢞ࢫࢆ඘ሸࡋࡓࢭࣝࢆᐃ

acquired by (a) Oldfield Echo and (b) Single㟁Ẽ⅔࡟ධࢀࠊࡑࢀࡒࢀ 40, 60, 80, 100, 120, 150 ºC ࡛ 6 ᪥㛫㓟໬

Pulse.

ࡉࡏࡿࡇ࡜࡟ࡼࡾ㓟໬Ⅳࢆᚓࡓࠋᅛయ 17O MAS NMRᐃ࡟ࡣࠊ㟼☢ሙᙉᗘ 16.45 T㸦17O ࡢඹ㬆࿘Ἴᩘ㸸84.829 MHz㸧ࡢ㉸㟁ᑟ࣐ࢢࢿ

ࢵࢺࠊJEOL ECA 700 ศගィࢆ⏝࠸ࡓࠋヨᩱ⟶⏤᮶ࡢ 17O ࣂࢵࢡࢢࣛ࢘ࣥࢻࢩࢢࢼࣝࢆ᤼㝖ࡍࡿࡓࡵࠊ
Si3N4 〇ࡢ 4 mmI ヨᩱ⟶࠾ࡼࡧ CPMAS Probe ࢆ⏝࠸ࡓࠋࡲࡓࠊࣉ࣮ࣟࣈࡢ⟂య᣺ື࡟క࠺ࣜࣥࢠࣥࢢ
ࢆపῶࡋࠊࢫ࣌ࢡࢺࣝࡢ࠺ࡡࡾࢆᢚไࡍࡿࡓࡵࠊOldfield Echo ἲ 6) ࢆ⏝࠸ࡓࠋOldfield Echo ἲࡣࠊᇶᮏ
ⓗ࡟ࡣ Hahn Echo 7) ἲ࡜ྠᵝ࡛࠶ࡿࡀࠊ16 ẁ㝵ࡢ఩┦ᅇࡋࢆ౑⏝ࡋࡓࣃࣝࢫࢩ࣮ࢣࣥࢫ࡛࠶ࡿࠋヨᩱᅇ㌿࿘Ἴᩘࡣ 18 kHzࠊRF ࣃ࣮࣡ࡣ 156.25 kHzࠊࣃࣝࢫ⧞ࡾ㏉ࡋ᫬㛫ࡣ 0.2 s ࡟タᐃࡋࠊእ㒊ᶆ‽࡜ࡋ࡚ H217O ࢆ⏝࠸ࡓࠋ࢚ࢥ࣮ࡢ᫬㛫ࡣᅇ㌿ྠᮇࡉࡏW1= W2= 55.56 Ps ࠊ✚⟬ᅇᩘࡣ 108320 ᅇ࡟タᐃࡋࡓࠋࡉࡽ࡟ࠊ17O-Multiple Quantum Magic Angle Spinning (MQMAS) NMR ࢫ࣌ࢡࢺࣝ

ᐃ 8)ࡋ㓟⣲ᐁ⬟ᇶࢆᖐᒓࡍࡿࡇ࡜࡛ࠊࡼࡾヲ⣽࡞㓟໬཯ᛂᶵᵓࡢゎ᫂ࢆヨࡳࡓࠋ17O 3QMAS NMR ࢫ࣌ࢡࢺࣝ

ᐃ࡟ࡣ Soft

pulse added mixing (SPAM) 3QMAS ࢩ࣮ࢣࣥࢫࢆ⏝࠸ࡓࠋヨᩱᅇ㌿࿘Ἴᩘࡣ 18 kHz ࡜ࡋࠊࣁ࣮ࢻࣃࣝࢫ
㸦HP1, HP2㸧ࢆ RF ᙉᗘ 200.3 kHz ࡟࡚ HP1= 4.2 Ps, HP2= 1.2 Ps ࡜ࡋࠊࢯࣇࢺࣃࣝࢫ㸦SP1㸧ࡣࠊRF ᙉ
ᗘ 66.7 kHz ࡟࡚ SP1= 15 Ps ࡜ࡋࡓࠋࡲࡓࠊt1 ࡢྲྀࡾ㎸ࡳ᫬㛫ࡣ 1.28 ms, ほ17

ᖜࡣ 72 kHz, ࣃࣝࢫ⧞ࡾ

㏉ࡋ᫬㛫ࡣ 0.2 ms ࡟タᐃࡋࠊ1072000 ᅇ✚⟬ࡋࡓࠋ㧗ឤᗘᅛయ O MAS NMRᐃ࡟ࡣࠊ㟼☢ሙᙉᗘ17

18.8 T㸦 O ࡢඹ㬆࿘Ἴᩘ㸸108.488 MHz㸧ࡢ㉸㟁ᑟ࣐ࢢࢿࢵࢺࠊBruker ASCEND 800 ศගィࠊ3.2 mm I
Cryo-MAS-Probe ࢆ⏝࠸ࡓࠋヨᩱᅇ㌿࿘Ἴᩘࡣ 15 kHzࠊRF ࣃ࣮࣡ࡣ 172.4 kHzࠊ✚⟬ᅇᩘࡣ 16,000 ᅇ࡟タᐃࡋࡓࠋࡇࡇ࡛ࡣࠊprojection Magic Angle Turning – Phase Adjusted Spinning Sideband㸦pjMATPASS㸧9)ࡢࣃࣝࢫࢩ࣮ࢣࣥࢫࢆ⏝࠸ࠊࢫࣆࢽࣥࢢࢧ࢖ࢻࣂࣥࢻࡢᾘཤࢆ᳨ウࡋࡓࠋࡇࡢ࡜ࡁࡢࣃࣝࢫ⧞ࡾ㏉ࡋ᫬㛫ࡣ 0.5 s ࡟タᐃࡋࡓࠋࡲࡓࠊẚ㍑ࡢࡓࡵ࡟ Hahn Echo ࡢࣃࣝࢫࢩ࣮ࢣࣥࢫࢆ⏝࠸࡚ 17O MAS NMRࢫ࣌ࢡࢺࣝࢆྲྀᚓࡋࡓࠋࡇࡢ࡜ࡁࡢࣃࣝࢫ⧞ࡾ㏉ࡋ᫬㛫ࡣ 0.5 s ࡟タᐃࡋࡓࠋ[3] ⤖ᯝ࠾ࡼࡧ⪃ᐹ
 Fig. 1 ࡟㓟໬Ⅳࡢ 17O NMR ࢫ࣌ࢡࢺࣝࢆ♧ࡍࠋᅗ୰ࡢ㯮⥺࠾ࡼࡧ㉥⥺ࡣࠊࡑࢀࡒࢀ Single Pulse, Oldfield
Echo ἲ࡛

ᐃࡋࡓࢫ࣌ࢡࢺ࡛ࣝ࠶ࡿࠋࡇࢀ࡟ࡼࡾࠊOldfield Echo ἲ࡛ᐃࡍࡿࡇ࡜࡟ࡼࡗ࡚ࠊࣜࣥࢠ

ࣥࢢࡀゎᾘࡉࢀࡿࡇ࡜ࡀࢃ࠿ࡗࡓࠋࡲࡓࠊFig.2 ࠿ࡽࠊ㓟໬Ⅳ࡟ࡣᑡ࡞ࡃ࡜ࡶ 2 ࡘࡢࢢ࣮ࣝࣉࡢ㓟⣲ᐁ⬟ᇶ㸦site A, B㸧ࡀࠊ40 ºC ࡢప࡟࠾࠸࡚ࡶ⏕ᡂࡋࡓ࡜⪃࠼ࡽࢀࡿࠋ࡞࠾ࠊ໬Ꮫࢩࣇࢺ್ 4) ࠿ࡽ site Aࡣ࢔ࣝࢥ࣮ࣝࡸ㐣㓟໬≀ࠊsite B ࡣ࢔ࣝࢹࣄࢻᇶࡸ࢝ࣝ࣎࢟ࢩࣝᇶ࡛࠶ࡿྍ⬟ᛶࡀ♧၀ࡉࢀࡓࠋࡉࡽ࡟ࠊ
㓟໬ᗘࡢୖ᪼࡟క࠸ࢫ࣌ࢡࢺࣝࡢ S/N ẚࡀྥୖࡋࡓࡇ࡜࠿ࡽࠊ▼Ⅳ࡟྾╔ࡋࡓ㓟⣲㔞ࡀቑຍࡋࡓࡇ

࡜ࡀࢃ࠿ࡗࡓࠋࡇࡢࡇ࡜ࡣࠊྠࡌ㓟໬᫬㛫ࡢୗ࡛ࡣࠊ㓟໬࠾ࡾࠊ㐣ཤ▱ぢ 2) ࡜ࡶ୍⮴ࡋࡓࠋࡲࡓࠊOldfield echoᗘࡢୖ᪼࡟క࠸㓟໬ࡀ㐍ࡴࡇ࡜ࢆ♧၀ࡋ࡚ᐃ࡟ࡼࡗ࡚ᚓࡽࢀࡓ 1 ḟඖࡢ NMR ࢫ࣌ࢡࢺࣝ

－ 175 －

࠿ࡽࡣࠊ㓟໬ࡣほᗘࡢୖ᪼࡟క࠺᪂ࡓ࡞㓟⣲ᐁ⬟ᇶࡢᙧᡂࡉࢀ࡞࠿ࡗࡓࠋࡉࡽ࡟ࠊ㓟໬Ⅳ࡟⏕ᡂࡋࡓ site

A/site B ࡢẚ⋡ࢆ Fig. 3 ࡟♧ࡋࡓࠋࡑࡢ⤖ᯝࠊsite A/ siteB ࡣ 40, 60, 70 ºC ࡛ࡣ⣙ 0.6 ࡔࡗࡓࡀࠊ

ᗘୖ᪼࡟క࠸

site A/ site B ࡣୖ᪼ࡋࠊ80, 100, 120, 150 ºC ࡛ࡣ 1.0, 1.1,
1.2, 1.4 ࡜࡞ࡗࡓࠋ㐣ཤ▱ぢ 1) ࡛ࡣࠊ▼Ⅳ࡜཯ᛂࡋࡓእ㒊⏤᮶ࡢ㓟⣲ࡣࠊࡲࡎࠊ࢔ࣝࢥ࣮ࣝࡸ㐣㓟໬≀࡜ࡋ࡚▼Ⅳ୰࡟ᅛᐃ໬ࡉࢀࠊ⥆࠸࡚ࠊࡇࢀࡽࡀ࢔ࣝࢹࣄࢻᇶࡸ࢝ࣝ
࣎࢟ࢩࣝᇶ࡬࡜ኚ໬ࡍࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿࡇ࡜࠿ࡽࠊᮏ
ᐇ㦂ࡣ site A ࡀ㓟໬཯ᛂࡢ㐍⾜࡜࡜ࡶ࡟ site B ࡬࡜ኚ໬Fig. 2 17O MAS NMR spectra of oxidized coal.

ࡋࡓྍ⬟ᛶࡀ♧၀ࡉࢀࠊWang ࡽࡀ♧ࡋࡓ▼Ⅳࡢ㓟໬཯ᛂᶵᵓ 2) ࢆᨭᣢࡍࡿ⤖ᯝ࡜࡞ࡗࡓࠋ
ḟ࡟ࠊ60|C ࠾ࡼࡧ 150|C ࡛ㄪ〇ࡋࡓ㓟໬Ⅳࡢ 17O
3QMAS NMR ࢫ࣌ࢡࢺࣝࢆ Fig.4 (a), (b)࡟♧ࡍࠋ60|C
࡛ㄪ〇ࡋࡓ㓟໬Ⅳ࡟ࡣࠊ୺࡟ࣄࢻࣟ࢟ࢩᇶ࡜ࠊ஧㔜⤖ྜᛶࡢ㓟⣲ࡢࡳࡀ 17O ࡛࠶ࡿ࢝ࣝ࣎࢟ࢩࣝᇶࡀ⏕ᡂࡋࡓࡇ࡜ࡀࢃ࠿ࡗࡓࠋ୍᪉ࠊ150|C ࡛ㄪ〇ࡋࡓ㓟໬Ⅳ࡟ࡣ஧㔜⤖ྜᛶࡢ㓟⣲ࠊ࠾ࡼࡧࠊ༢⤖ྜᛶࡢ㓟⣲ࡢ୧⪅ࡀ 17O ࡛࠶ࡿ࢝ࣝ࣎࢟ࢩࣝᇶࡀ⏕ᡂࡋࡓࡇ࡜ࡀࢃ࠿ࡗ
ࡓࠋࡇࡢࡇ࡜࠿ࡽࠊ60|C ࡛⏕ᡂࡋࡓ࢝ࣝ࣎࢟ࢩࣝᇶࡢ

Fig. 3 Estimated site B/ site A ratio in oxidized coal.

ከࡃࡣඖ᮶▼Ⅳ࡟ྵࡲࢀࡿࣄࢻࣟ࢟ࢩᇶࡲࡓࡣ࢔ࣝࢹࣄࢻᇶ⏤᮶࡛࠶ࡿࡢ࡟ᑐࡋࠊ150|C ࡛⏕ᡂࡋࡓ࢝ࣝ࣎࢟ࢩࣝᇶࡣ㓟໬࡟ࡼࡗ࡚⏕ᡂࡋࡓࣄࢻࣟ࢟ࢩᇶࡀࡉࡽ࡟㓟໬ࡉࢀ࡚⏕ᡂࡋࡓࡶࡢ࡛࠶ࡿࡇ࡜ࡀ
ุ᫂ࡋࡓࠋ

Fig. 4 17O 3QMAS NMR spectra of oxidized coal prepared at (a) 60ºC and (b) 150ºC.

－ 176 －

ࡉࡽ࡟ࠊCryo-MAS-Probe ࢆ⏝࠸࡚ pjMATPASS ࡛ᐃࡋࡓ࡜ࡇࢁࠊFig.5 ࡟♧ࡍ SSB ࡀᾘཤࡉࢀࡓ 17O
NMR ࢫ࣌ࢡࢺࣝࢆ 35 ᫬㛫࡛ྲྀᚓ࡛ࡁࠊᐊ

ࣉ࣮ࣟࣈ࡜ẚ㍑ࡍࡿ࡜⣙ 1/8 ࡟▷⦰࡛ࡁࡓࠋࡑࡢ⤖ᯝࠊsite B ࡟ࡣ࢝ࣝ࣎࢟ࢩࣝᇶࡔࡅ࡛࡞ࡃ࢔ࣝࢹࣄࢻᇶ
⏤᮶ࡢࢩࢢࢼࣝࡶ᫂☜࡟☜ㄆ࡛ࡁࡿࡼ࠺࡟࡞ࡗࡓࠋ
࢔ࣝࢹࣄࢻᇶࡣࠊHahn Echo ἲ࡛ࡣࢫࣆࢽࣥࢢࢧ࢖
ࢻ࡟ᇙࡶࢀ࡚ほฟ᮶࡚࠸࡞࠿ࡗࡓࡓࡵࠊ

pjMATPASS ࡟ࡼࡗ࡚ึࡵ࡚ほ࡛ࡁࡓ࡜ゝ࠼ࡿࠋ

17௨ୖࡢࡇ࡜࠿ࡽࠊ O2 㞺ᅖẼୗ࡛ㄪ〇ࡋࡓ㓟໬Ⅳ
ࡢ 17O MAS NMRᐃ࡟ࡼࡾࠊ㓟໬࡟ࡼࡗ࡚᪂ࡓ࡟

⏕ᡂࡋࡓ㓟⣲ᐁ⬟ᇶࢆ┤᥋ほ࡛ࡁࠊ▼Ⅳࡢ㓟໬཯ᛂᶵᵓࢆヲ⣽࡟᳨ウ࡛ࡁࡿࡼ࠺࡟࡞ࡗࡓࠋ
[4] ⤖ゝ
 ▼Ⅳࢆ 17O2 㞺ᅖẼୗ࡛㓟໬ࡉࡏࠊᅛయ 17O MAS
NMR ࢫ࣌ࢡࢺࣝ

ᐃࢆ⾜ࡗࡓࠋOldfield Echo ἲ࡛ᐃࡋࡓ࡜ࡇࢁࠊࣜࣥࢠࣥࢢࡢᑡ࡞࠸Ⰻዲ࡞ࢫ࣌ࢡࢺ

Fig. 5 17O MAS NMR spectra of oxidized coal at 80ºCࣝࡀᚓࡽࢀࠊ㓟໬Ⅳ࡟ࡣᑡ࡞ࡃ࡜ࡶ஧✀㢮ࡢ㓟⣲ᐁacquired by (a) pjMATPASS with 1H decoupling, (b)⬟ᇶ Site A, B ࡀ⏕ᡂࡋࡓࡇ࡜ࡀࢃ࠿ࡗࡓࠋ㓟໬Hahn echo with 1H decoupling and (c) Hahn echo withᗘࢆኚ໬ࡉࡏࡓ࡜ࡇࢁࠊ⏕ᡂࡋࡓ㓟⣲ᐁ⬟ᇶࡢ✀㢮࡟

non- 1H decoupling sequence.

ኚ໬ࡣ࡞࠿ࡗࡓࡀࠊྲྀࡾ㎸ࡲࢀࡓ㞺ᅖẼ⏤᮶ࡢ㓟⣲ࡢ⤖ྜ఩⨨ࡀ␗࡞ࡾࠊࡲࡓࠊ㧗࡯࡝⏕ᡂ㔞ࡀከ࠸ࡇ࡜ࡀࢃ࠿ࡗࡓࠋࡉࡽ࡟ࠊCryo-Mas-Probe ࡟ࡼࡿ㧗ឤᗘ໬ࡸ pjMATPASS ࡢࣃࣝࢫࢩ࣮ࢣࣥࢫࡢ᥇⏝࡟ࡼࡿࢫࣆࢽࣥࢢࢧ࢖ࢻࡢᾘཤࠊ17O-MQMAS ➼㧗ศゎ⬟ 2 ḟඖ NMR ࢫ࣌ࢡࢺࣝ

ᐃ࡟ࡼࡿ㓟⣲ᐁ⬟ᇶࡢྠᐃ࡟ࡼࡗ࡚ࠊヲ⣽࡞▼Ⅳࡢ㓟໬཯ᛂゎᯒࡀ㐍

17ࡴ࡜⪃࠼ࡽࢀࡿࠋᚑࡗ࡚ࠊ O2 ⃰⦰࢞ࢫࢆ⏝࠸ࡓヨᩱㄪ〇࡜ᅛయ 17O MAS NMR ࢫ࣌ࢡࢺࣝ

ᐃࡢ⤌ࡳྜࢃࡏࡣࠊ▼Ⅳࡢ㓟໬཯ᛂᶵᵓࢆゎᯒࡍࡿୖ࡛㔜せ࡞ࢶ࣮ࣝ࡟࡞ࡿ࡜⪃࠼ࡽࢀࡿࠋ
References
1) I, Miyagawa, Y. Yamada, J. Inaba, Nenryokyokaishi, 1929, 8, 883.
2) H. Wang, Z. D. Bogdan and E. M. Kennedy, Progress in Energy and Combustion Science, 2003, 29, 487.
3) M. Uchida, Dissertation, 2018, 49.
4) G. Wu, Progress in Nuclear Magnetic Resonance Spectroscopy, 2008 52, 118.
5) K. Kanehashi, K. Shimoda, K. Saito, Tetsu-to-Hagane, 2009, 95 321.
6) A. C. Kunwar, G. L. Turner and E. Oldfield, Journal of magnetic resonance, 1986, 69, 124.
7) H. Y. Carr, E. M. Purcell, Physical Review, 1954, 94, 630.
8) J. P. Amoureux, C.

Fernandez and S. Steuernagel, Journal of magnetic resonance, 1996, 123, 116.

9) I. Hung, I. Zhou, F. Pourpoint, C. P. Grey and Z. Gan, J. Am. Chem.Soc. 2012, 134, 1898.

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P21

Magnetically manipulated goniometer‫ୖۑ‬ฟ཭ဢ㸪Ṋ⏣࿴⾜11ி㒔኱Ꮫ኱Ꮫ㝔⌮Ꮫ◊✲⛉໬Ꮫᑓᨷ

Magnetically manipulated goniometer‫ۑ‬Tomoya Kamide1, Kazuyuki Takeda1
1 Division of Chemistry, Graduate School of Science, Kyoto University

We propose a strategy to reorient magnetically oriented crystals in an arbitrary direction with respect tothe external magnetic field, opening the possibility of applying magnetically oriented microcrystal
suspension (MOMS) to characterization of anisotropic nuclear spin interactions.(a)[Introduction]☢໬⋡␗᪉ᛶࢆ᭷ࡍࡿ⤖ᬗࡣࠊኚㄪᅇ㌿☢ሙࢆ⏝࠸࡚㓄ྥࡉࡏࡿࡇ࡜ࡀ࡛ࡁࡿࠋᐇ㝿࡟ᙉ☢ሙࢆᅇ㌿ࡉࡏࡿࡇ࡜ࡣᢏ⾡ⓗ࡟ᅔ㞴࡛࠶ࡿࡀࠊ௦ࢃࡾ࡟ࠊ㟼☢ሙ୰࡛⤖ᬗࢆᾋ࠿ࡏࡓ⢓ᛶ፹యࢆධࢀࡓヨᩱ⟶ࢆኚㄪᅇ㌿ࡉࡏࡿ࡜ࠊ୍ᐃ᫬㛫ࡢᚋ࡟
ヨᩱ⟶࡟ᅛᐃࡉࢀࡓᗙᶆ⣔࡛⤖ᬗࡀ㸱ḟඖ㓄ྥࡍࡿ[1]ࠋ୍
᪉ࠊNMR ᐃ࡟ࡼࡿ᰾ࢫࣆࣥ┦஫స⏝ࢸࣥࢯࣝࡢ࢟ࣕࣛࢡ
ࢱࣜࢮ࣮ࢩࣙࣥ࡟ᛂ⏝ࡍࡿࡓࡵ࡟ࡣࠊእ㒊☢ሙ࡟ᑐࡍࡿ⤖ᬗࡢ㓄ྥࢆࢥࣥࢺ࣮ࣟࣝࡍࡿࡇ࡜ࡀᚲせ࡛࠶ࡿࠋ☢Ẽ㓄ྥ࡟⏝࠸ࡿヨᩱᅇ㌿ᶵᵓࢆࡑࡢࡲࡲ⏝࠸࡚ࠊ㓄ྥࡀ⇕ⓗ࡟ᩓ㐓ࡋ࡚࠸ࡃ㐣⛬ࡼࡾࡶ༑ศᡭ᪩ࡃNMR ᐃࢆ⾜࠺ࡇ࡜࡛ࠊᅇ㌿ࣃ(b)ࢱ࣮ࣥࢆ ᐃࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡋ࠿ࡋࠊᅇ㌿ࣃࢱ࣮ࣥࢆ
ᐃ࡛ࡁࡿࡢࡣ㓄ྥࡢࡓࡵࡢヨᩱᅇ㌿㍈࿘ࡾ࡟㝈ࡽࢀࡿࠋࡇࡇ
࡛ᡃࠎࡣࠊ☢Ẽⓗ࡟㓄ྥࡋࡓ⤖ᬗࢆእ㒊☢ሙ࡟ᑐࡋ࡚௵ពࡢ
᪉ྥ࡟ഴࡅ࡚NMR ᐃࢆ⾜࠺ࡇ࡜ࡢ࡛ࡁࡿ࢔ࣉ࣮ࣟࢳࢆᥦ
᱌ࡍࡿࠋ[Principle]ࡇࡇ࡛ࡣ཯☢ᛶ⤖ᬗ࡟࠾ࡅࡿ☢໬⋡ࢸࣥࢯࣝࡢ୺್߯ଵ ߯ଶ ߯ଷ ࡢ኱ᑠ㛵ಀࡀࠊͲ ൐ ߯ଵ ൐ ߯ଶ ൐ ߯ଷ ࡛࠶ࡿ࡜ࡍࡿࠋヨᩱ⟶࡟Fig. 1. A proposed scheme for (a)ᅛᐃࡉࢀࡓᗙᶆ⣔࡟࠾࠸࡚ࠊኚㄪᅇ㌿☢ሙࡢ㌶㊧ࢆᴃ෇࡛㏆

magnetic alignment of crystals withఝࡍࡿ࡜ࠊ⤖ᬗࡣᴃ෇ࡢ㛗㍈ࡀ߯ଵ ㍈ࠊ▷㍈ࡀ߯ଶ ㍈ࠊࡑࡋ࡚ᅇ

frequency modulated rotation of the㌿㍈ࡀ߯ଷ ㍈࡟୍⮴ࡍࡿ᪉ྥ࡟ഴࡃࠋࡼࡗ࡚ࠊ୍ᐃ᫬㛫ࡢᚋ࡟

sample together with the holder,☢Ẽ㓄ྥࡀ㐩ᡂࡉࢀࡿ࡜ࠊ߯ଷ ㍈ࡀヨᩱࡢᅇ㌿㍈᪉ྥ࡟ᥞ࠺ࠋ

followed by (b) another rotation ofࡑࡢᚋࠊ߯ଷ ㍈࿘ࡾࡢᅇ㌿ࣃࢱ࣮ࣥࢆ ᐃࡍࡿࡇ࡜ࡣᐜ࡛᫆࠶

the inner sample tube alone.

ࡿࠋࡉࡽ࡟ࠊ߯ଷ ㍈࡟ᆶ┤࡞㍈ࡢ࿘ࡾ࡟ࡶᅇ㌿ࢆ᪋ࡍࡇ࡜ࡀ࡛
ࡁࡿࡼ࠺࡟ࡍࡿࡓࡵࡢ࢔࢖ࢹ࢔ࢆᅗ㸯࡟♧ࡍࠋmagnetic susceptibility (☢໬⋡), single crystal (༢⤖ᬗ), Magnetically Oriented Microcrystal Suspension(MOMS)‫ࡸࡶ࡜࡛ࡳ࠿ۑ‬㸪ࡓࡅࡔ࠿ࡎࡺࡁ

－ 178 －

⤖ᬗࢆᾋ࠿ࡏࡓ⢓ᛶ፹యࢆධࢀࡿヨᩱ⟶ࢆࠊヨᩱ(a)⟶࣍ࣝࢲ࣮࡟ධࢀࠊヨᩱ⟶࣍ࣝࢲ࣮ࢆ☢ሙ࡟ᆶ┤࡞㍈࿘ࡾ࡟ኚㄪᅇ㌿ࡉࡏࡿࠋ࣍ࣝࢲ࣮ࡢኚㄪᅇ㌿ࡢ௙᪉࡟㑅ᢥ⫥ࡀ࠶ࡾࠊヨᩱ࠿ࡽぢࡓ☢ሙࡢ㏆ఝ
ⓗ࡞ᴃ෇ᅇ㌿ࡢ㛗㍈ࢆヨᩱ⟶ࡢ᪉ྥ࡟タᐃࡍࢀࡤࠊࢡࣛࢵࢳ࡟ࡼࡗ࡚߯ଵ ㍈ࢆᅇࡍࡇ࡜ࡀ࡛ࡁࡿࠋࡲ
ࡓ▷㍈ࢆタᐃࡍࢀࡤࠊ߯ଶ ㍈ࢆᅇࡍࡇ࡜ࡶྍ⬟࡜࡞ࡿࠋࡋࡓࡀࡗ࡚ࠊ☢ሙ࡟ᑐࡋ࡚௵ពࡢ᪉ྥ࡟㓄ྥ࡛ࡁࡿࠋ[Development]ࡲࡎࠊ☢Ẽ㓄ྥࢆ෌⌧ࡍࡿࡓࡵࡢࣉ࣮ࣟࣈࢆ㛤Ⓨࡋࡓࠋᅇ㌿ࡢ㥑ືࡢࡓࡵ࡟ࢫࢸࢵࣆࣥࢢ࣮ࣔࢱ
ࢆᑟධࡋࠊaruduinoࢆ⏝࠸࡚ไᚚࡋࡓࠋࢫࢸࢵࣆ
ࣥࢢ࣮ࣔࢱࡣ㉸㟁ᑟ☢▼ࡢ┤ୗ࠿ࡽ⣙1 m㞳ࡋ࡚(b)㓄⨨ࡋࠊࢩࣕࣇࢺ࡜ࣘࢽࣂ࣮ࢧࣝࢪࣙ࢖ࣥࢺࠊ࠾
ࡼࡧചṑ㌴ࢆ௓ࡋ࡚☢ሙ୰ࡢ8 mmࡢヨᩱ⟶࡟ఏ㐩ࡋࡓࠋࢥ࢖ࣝࡣ300ࠊ75ࠊ20 MHzᖏ࡛୕㔜࡟࢖ࣥࣆ࣮
ࢲࣥࢫ࣐ࢵࢳࣥࢢࡉࡏࠊ7 T࡛1H-13C-14N୕㔜ඹ㬆ࢆ⾜࠼ࡿࡼ࠺࡟ࡋࡓࠋᅗ2࡟ࠊ☢Ẽ㓄ྥࡉࡏྲྀᚓ
ࡋࡓ10% 1-13C L-࢔ࣛࢽࣥࡢ༢⤖ᬗࡢ13C࠾ࡼࡧࠊࢢࣜࢩࣥࡢ༢⤖ᬗࡢ14Nࡢࢫ࣌ࢡࢺࣝࡢ౛ࢆ♧ࡍࠋࢡࣛࢵࢳࡢ㛤Ⓨ࡜ࠊ☢Ẽ㓄ྥࢩࢫࢸ࣒࡜ࡢ⤫ྜࡀ௒ᚋࡢㄢ㢟࡛࠶ࡿࠋ
Fig. 2. (a)13C NMR spectra of a magneticallyoriented single crystal of 10% 1-13C L-alanine.
(b) 14N NMR spectra of magnetically oriented
single crystal of glycine. The data wereacquired in 7 T at room temperature forvarious angles ߠ between the ߯ଵ axis of themagnetic-susceptibility tensor and the external
field.
Reference[1] Kusumi R, Kadoma H, Wada M. et al., Journal of Magnetic Resonance 309 (2019) 106618.

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P22Y

㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒࡟ࡼࡿRFࢥ࢖ࣝࡢ᭱㐺໬タィཬࡧホ౯ἲࡢ㛤Ⓨ‫ࢺࢵࢩࢸ ࣮ࣥ࢝ࣛࢺࣜࢺ ۑ‬㸪ᒣᮏ⯟㍤㸪㧗ᶫ㞞ே2㸪ᒸᮧဴ⮳1ᮾிᕤᴗ኱Ꮫ ᕤᏛ㝔 ᶵᲔ⣔2⌮໬Ꮫ◊✲ᡤ ⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮Development of optimization design and evaluation method for RF coils using genetic
algorithms‫ ۑ‬TRITRAKARN Techit 1, YAMAMOTO Kouki1, TAKAHASHI Masato2, OKAMURA
Tetsuji1
1 Department of Mechanical Engineering, Tokyo Institute of Technology
2Laboratory for NMR Engineering and Structural Science, RIKEN Center for Biosystems Dynamics Research

An electromagnetic field simulation that can apply genetic algorithms to optimize the shape of RF coils
for NMR/MRI was developed. C++ is used to calculate the B1 magnetic field from an arbitrary coil geometry
to predict the 90-degree pulse length and signal intensity. The optimization of the planar RF coil wasdemonstrated to obtain the NMR signal most efficiently from the combination of 250 wires in the coil. The
signal intensity of the designed RF coil and a dimensionally optimized solenoid coil with the same sample
volume size were compared to evaluate the performance in the simulation and the NMR measurement. The
signal intensity ratio against the optimized solenoid coil named "Optimized Solenoid signal strength Ratio(OSR)" is proposed as a new evaluation parameter of RF coils. The demonstration experiments were
performed by 14N NMR measurement using a 500 MHz NMR magnet and a home-built spectrometer.

NMR/MRIࡢ ᐃ࡟࠾࠸࡚RFࢥ࢖ࣝࡣ୙ྍḞ࡛࠶ࡿࠋRFࢥ࢖ࣝ࡟ồࡵࡽࢀࡿᛶ⬟ࡣ࠸࠿࡟ ᐃヨᩱ࡟ᙉࡃ࠿ࡘᆒ୍࡞㧗࿘Ἴ☢ሙࢆ↷ᑕ࡛ࡁࡿ࠿ࡀ㔜せ࡛࠶ࡾࠊࡑࢀ࡟ࡶࡗ࡜ࡶ㐺ࡋࡓᙧ≧ࡣࢯ
ࣞࣀ࢖ࢻRFࢥ࢖࡛ࣝ࠶ࡿࠋࡓࡔࡋࠊᐇ㝿ࡢNMR࡛ࡣヨᩱࡢᙧ≧ࡣࡉࡲࡊࡲ࡛࠶ࡾࠊࡲࡓ⏝㏵࡟
ࡼࡗ࡚RFࢥ࢖ࣝࡀ㓄⨨࡛ࡁࡿ✵㛫ࡀไ㝈ࡉࢀࡿࡓࡵࠊࡑࡢ㒔ᗘRFࢥ࢖ࣝࡢᙧ≧ࢆࢹࢨ࢖ࣥࡍࡿᚲせࡀ࠶ࡿࠋࡇࡢࡼ࠺࡞ᙧ≧ࡢ᭱㐺໬ࢆࢩ࣑࣮ࣗࣞࢩࣙࣥ࡟ࡼࡗ࡚⾜࠺᪉ἲࡢࡦ࡜ࡘ࡜ࡋ࡚ࠊ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒㸦Genetic algorithms, GA㸧ࡀ࠶ࡆࡽࢀࡿࠋ
㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࡣ㐍໬ㄽⓗ࡞⪃࠼᪉࡟ᇶ࡙࠸࡚ࢹ࣮ࢱࢆ᧯సࡋࠊ᭱㐺ゎࢆ᥈⣴ᡭἲ࡛࠶ࡿࠋせ⣲ࡀከࡃ࡞ࡿ࡜ᣦᩘ㛵ᩘⓗ࡟⤌ࡳྜࢃࡏᩘࡀከࡃ࡞ࡿ⤌ྜࡏ᭱㐺໬ၥ㢟ࢆゎỴࡍࡿࡓࡵ࡟
≉࡟౑ࢃࢀ࡚࠸ࡿࠋRFࢥ࢖ࣝᙧ≧ࡢ᭱㐺໬タィࢆ⤌ࡳྜࢃࡏၥ㢟࡟ኚ᥮࡛ࡁࢀࡤࠊ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࢆᑟධࡍࡿࡇ࡜࡛⪃࠼ࡽࢀࡿ࡯ࡰ↓㝈ࡢ⤌ࡳྜࢃࡏ࠿ࡽ▷᫬㛫࡛ຠ⋡ⓗ࡟᭱㐺ゎࢆᑟࡃࡇ࡜ࡀ࡛ࡁࡿ࣓ࣜࢵࢺࡣ࠶ࡿࠋNMR/MRIࡢRFࢥ࢖ࣝࡢᙧ≧ࢆ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࢆ⏝࠸࡚᭱㐺໬ࢆ⾜࠺◊✲ሗ࿌1,2ࡀࡇࢀࡲ࡛࡟࠶ࡗࡓࡀࠊ࠶ࡿ≉ᐃࡢᙧ≧ࡢࢥ࢖ࣝ࢖ࣥࢲࢡࢱࣥࢫ‫ࡢܮ‬ィ⟬ᘧࢆ⏝࠸ࠊỴࡲࡗࡓࢥ࢖ࣝᙧ≧ࡢ㓄⨨ࡸࢧ࢖ࢬࡢࣃ࣓࣮ࣛࢱࡋ࠿᭱㐺࡛ࡁ࡞࠸ไ⣙ࡀᏑᅾࡋࡓࡓࡵࠊ᭱㐺໬࡛ࡁࡿࢥ࢖ࣝᙧ≧ࡀ㝈ᐃࡉࢀ࡚࠸ࡓࠋ
㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒㸪RFࢥ࢖ࣝ㸪᭱㐺໬ࢯࣞࣀ࢖ࢻಙྕᙉᗘẚ‫ࢺࢵࢩࢸ ࣮ࣥ࢝ࣛࢺࣜࢺۑ‬㸪ᒣᮏ⯟㍤㸪㧗ᶫ㞞ே 㸪ᒸᮧဴ⮳－ 180 －

ᮏ◊✲࡛ࡣࠊ௵ពࡢRFࢥ࢖ࣝᙧ≧࡟ࡘ࠸࡚᭱㐺໬タィࡀ࡛ࡁࡿࡼ࠺࡟ࠊỗ⏝ᛶࡢ࠶ࡿᙧ࡛㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࡀ㐺⏝࡛ࡁࡿ㟁☢⏺ࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ㛤Ⓨࡋࡓࠋ☢ሙศᕸࡢィ⟬࡟ࡣඛ⾜◊✲࡜ྠᵝ┤ὶࣔࢹࣝࢆ⏝࠸࡚࠸ࡿࡓࡵࠊἼ㛗ࡀၥ㢟࡟࡞ࡽ࡞࠸㸦ࢥ࢖ࣝ㛗ࡉࡀȢ/4ࡼࡾ▷࠸㸧ࠊࡘࡲࡾప࿘ἼᩘࡶࡋࡃࡣᑠᆺࡢRFࢥ࢖ࣝ࡟㐺⏝ྍ⬟࡛࠶ࡿࠋ౛࡜ࡋ࡚ᇶᯈRFࢥ࢖ࣝࡢᙧ≧ࢆỴࡵࡿ↓ᩘࡢ⥺㟁ὶࡢ⤌ࡳྜࢃࡏ࠿ࡽࠊ₃ࢀ☢ሙࢆῶࡽࡍࡇ࡜࡟ࡼࡗ࡚Filling Factorࢆྥୖࡉࡏࠊ
᭱ࡶຠ⋡ࡼࡃNMRಙྕࢆᚓࡿࡇ࡜ࡀ࡛ࡁࡿᙧ≧ࡢỴࡵ᪉ࢆ᱌ෆࡍࡿࠋ
ィ⟬࡟౑࠺PCࡢ㈇ᢸ࡜᫬㛫ࢆῶࡽࡍࡓࡵ࡟ࠊ༢⣧໬ࡋࡓ┤ὶࣔࢹࣝࢆ᥇⏝ࡍࡿࠋᇶᮏⓗ࡞ὶࢀࡣࠊ௵ពࡢRFࢥ࢖ࣝᙧ≧ࢆỴࡵࡿ⥺㟁ὶࡢ࣋ࢡࢺࣝࢆ㓄⨨ࡋࠊࣅ࣭࢜ࢧࣂ࣮ࣝࡢἲ๎࡛⥺㟁ὶࡀసࡿ☢ሙ࣋ࢡࢺࣝ‫ࢆܤ‬ィ⟬ࡍࡿࠋࢥ࢖ࣝࡢ࢖ࣥࢲࢡࢱࣥࢫ‫ࡣܮ‬඲✵㛫ࡢࡑࢀࡒࢀࡢ᱁ᏊⅬࡢ☢ሙ࢚ࢿࣝࢠ࣮ࡢ✚ศ࠿ࡽồࡵࡿࡓࡵ࡝ࡢࡼ࠺࡞ࢥ࢖ࣝᙧ≧࡛ࡶᑐᛂ࡛ࡁࡿࠋRFࢥ࢖ࣝ࠿ࡽ‫ܤ‬ଵࢆ↷ᑕࡍࡿ࡜ࡁ࡜ࡑࡢᚋࡢࢫࣆࣥࡢᣲືࡣࣈࣟࢵ࣍᪉⛬ᘧ࡟ࡼࡗ࡚ィ⟬ࡉࢀࠊບ㉳ࡉࢀࡓ☢໬࠿
ࡽRFࢥ࢖ࣝࡀཷಙ࡛ࡁࡿNMRಙྕᙉᗘࡣࣞࢩࣉࣟࢩࢸ࢕ࡢཎ⌮࡛ồࡵࡿࠋ ࡲࡓࠊHoult࡟ࡼࡿ࡜ࠊ௵ពࡢヨᩱయ✚㔞࡛ࡶࡗ࡜ࡶຠ⋡ࡼࡃNMRಙྕࢆᚓࡿࢯࣞࣀ࢖ࢻRFࢥ࢖ࣝࡢ᭱㐺࡞ᙧ≧ࡣ඲㛗/┤ᚄ㸻0.8ࠊࣆࢵࢳ/⥺ᚄ㸻1.5࡛࠶ࡿ3ࠋタィࡋࡓRFࢥ࢖ࣝࡢᛶ⬟ࢆබᖹ࡟ホ౯ࡍࡿ࡟ࡣࠊྠヨᩱ㔞࡛ᙧ≧᭱㐺໬ࡋࡓࢯࣞࣀ࢖ࢻRFࢥ࢖ࣝ࠿ࡽᚓࡓNMRಙྕᙉᗘ࡜ẚ㍑
ࡍࡿࠋࡇࡢẚ⋡ࢆࠕ᭱㐺໬ࢯࣞࣀ࢖ࢻಙྕᙉᗘẚࠖ㸦Optimized Solenoid signal strength Ratio,
OSR㸧࿧ࡧࠊRFࢥ࢖ࣝࡢ᪂ࡋ࠸ホ౯ἲ࡜ࡋ࡚ᥦ᱌ࡍࡿࠋ
㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࡣࢹ࣮ࢱ㸦ゎࡢೃ⿵㸧ࢆ㑇ఏᏊ࡛⾲⌧ࡋࡓࠕಶయࠖࢆ」ᩘ⏝ពࡋࠊ㐺ᛂᗘࡢ㧗࠸ಶయࢆඃඛⓗ࡟㑅ᢥࡋ࡚஺ཫ࣭✺↛ኚ␗࡞࡝ࡢ㑇ఏⓗ᧯సࢆ⧞ࡾ㏉ࡋ࡞ࡀࡽಶయࢆ㐍໬ࡉࡏࠊ㐺ᛂᗘࢆ᭱኱໬ࡍࡿಶయࡢゎࢆ᥈⣴ࡍࡿ࢔ࣝࢦࣜࢬ࣒࡛࠶ࡿࠋ㐺ᛂᗘ㛵ᩘࡣゎࡢೃ⿵ࢆᐃ㔞໬ࡋࠊ≉ᐃࡢ㑇ఏᏊࡀ௚ࡢ㑇ఏᏊࡼࡾඃࢀ࡚࠸ࡿࡇ࡜ࢆ♧ࡍ㛵ᩘ࡛࠶ࡿࠋᮏ◊✲ࡣ㑇ఏᏊࢆࢥ࢖
ࣝᙧ≧ࢆỴᐃࡍࡿ⥺㟁ὶ࡟ࠊ㐺ᛂᗘ㛵ᩘ࡜ࡋ࡚᭱㐺໬ࢯࣞࣀ࢖ࢻಙྕᙉᗘẚ⏝࠸ࡿࠋᮏ◊✲ࡢࢩ࣑࣮ࣗࣞࢩࣙࣥࡣC++ࡢ࢜ࣈࢪ࢙ࢡࢺᣦྥࡢタィᛮ᝿࡟ᇶ࡙࠸࡚ࢥ࢖ࣝᙧ≧ࢆỴࡵࡿ⥺㟁ὶࢡࣛࢫࠊ☢ሙࢡࣛࢫࠊヨᩱࢡࣛࢫࠊ᰾ࢫࣆࣥࢡࣛࢫࠊಙྕࢡࣛࢫࠊࡑࢀ࡜඲యࢆ⤫୍ࡍ
ࡿNMRࢩ࣑࣮ࣗࣞࢩࣙࣥࢡࣛࢫ࡛⟶⌮ࡍࡿࡓࡵࠊ௒ᅇ⏝࠸ࡓ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࣛ࢖ࣈ࣮ࣛࣜ4
࡜⼥ྜࡋࡸࡍ࠸ࠋ
ලయⓗ࡞㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ゎᯒࣔࢹࣝࡢึ

Initial stateᮇ≧ែ(Fig. 1)ࡣ㟼☢ሙ୰ᚰࡢᗙᶆ(0, 0, 0)࡟┤00 01 10 11

=

=

=

=

ᚄDࡢ2ḟඖࡢ෇ᙧࡢヨᩱ✵㛫ࢆタᐃࡋࠊᇶᯈ
RFࢥ࢖ࣝࡢᙧ≧ࢆỴࡵࡿྑࠊᕥྥࡁࡢ⥺㟁ὶ

D mm
z
y
x
1 mm

ࡣ㯮▮༳࡛♧ࡍࠋ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࡢ㑇ఏⓗ᧯సࢆ⾜࠺ࡓࡵ࡟ࠊ⥺㟁ὶࡢ≧ែࢆ2᱆ࡢ2㐍ᩘ

20 mm

Gap 0.4 mm

ࣅࢵࢺ࡜㐃ືࡉࡏࡿࠋyz㠃ᑐ⛠ࡢᣊ᮰᮲௳ࢆタ

30 mm

ᐃࡍࡿࡇ࡜࡟ࡼࡗ࡚ࠊ⥺㟁ὶࡢᮏᩘࡀ100࠿ࡽ
50ᮏ࡟࡞ࡾࠊ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒࡛250(1.12x1015) ࡢ⤌ࡳྜࢃࡏ࠿ࡽຠ⋡ࡼࡃ᭱㐺࡞⤌ࡳྜࢃࡏࢆㄪ࡭ࡿࡇ࡜࡟࡞ࡿࠋ0ୡ௦┠࡟ࡣ
50ಶࡢࣅࢵࢺࡢ⤌ࡳྜࢃࡏ(ಶయ)ࢆ100ಶ㸦100༉㸧ࣛࣥࢲ࣒࡟⏕ᡂࡋࠊࡑࢀࡒࢀࡢ≧ែࡢࣅࢵࢺࡢ⤌ࡳྜࢃࡏ࠿ࡽࡢRFࢥ࢖ࣝࡢ⥺㟁ὶ࡟ኚ

Fig. 1. The initial state of GA model
The presence or absence of line current isexpressed by 2-digit binary bits.

᥮ࡋࠊ⏕ᡂࡉࢀࡿ☢ሙ‫ܤ‬ଵ ࡜࢖ࣥࢲࢡࢱࣥࢫ‫ࢆܮ‬ィ⟬ࡍࡿࠋࡲࡓࠊ90ᗘࣃࣝࢫ㛗ࡢ࡜ࡁࡢ☢໬࣋ࢡ
ࢺࣝ࠿ࡽNMRಙྕᙉᗘ࡜OSRࢆィ⟬ࡋࠊ኱ࡁ࠸㡰࡟୪࡭ࡿࠋḟୡ௦࡟㐍໬ࡍࡿ࡜ࡁࡣ㑇ఏⓗ᧯సࡢ㑅ᢥࠊ஺ཫࠊ✺↛ኚ␗ࢆ⾜࠸ࠊࡑࡢ᪂ࡋ࠸⤌ࡳྜࢃࡏ࠿ࡽࡲࡓNMRಙྕ࡜OSRࢆィ⟬ࡋࠊ

－ 181 －

኱ࡁ࠸㡰࡟୪࡭ࡿࠋタᐃࡋࡓୡ௦ࡲ࡛ࡇࡢࡼ࠺࡞ィ⟬ࡢὶࢀࢆ⧞ࡾ㏉ࡍࠋึᮇ≧ែࡢࣛࣥࢲ࣒ࡢ
⤌ࡳྜࢃࡏ࡟ࡼࡗ࡚ࡣィ⟬⤖ᯝࡣ᭱኱್࡛ࡣ࡞ࡃᴟ኱್࡟␃ࡲࡗ࡚⤊஢ࡍࡿࡇ࡜ࡀ࠶ࡿࡓࡵࠊ
2000ୡ௦࡜5000ୡ௦ࡲ࡛ࡑࢀࡒࢀ2ᅇࡎࡘィ⟬ࢆ⾜࠸ࠊNMRಙྕᙉᗘ࡜OSRࡀ᭱኱࡟࡞ࡿ⤖ᯝࢆ㑅ࡪࠋィ⟬࡟౑⏝ࡋࡓPCࡣCPUࡀAMD Ryzen 9 3900X 3.80GHz࡛, 22 cores ࡛୪ิィ⟬࡛ࡁࡿࡼ
࠺࡟OpenMPࢆ౑⏝ࡋࡓࠋィ⟬᫬㛫ࡣ1000ୡ௦ᙜࡓࡾ1㹼1.5᫬㛫࡯࡝࠿࠿ࡿࠋ⣙1000ୡ௦࡛OSRࡀ୍ᐃ࡟࡞ࡾࠊᴟ኱್࠿ࡽᢤࡅࡔࡏ࡞ࡃ࡞ࡿࡀࠊ✺↛ኚ␗࡛ᴟ኱್࠿ࡽ᭱኱್ࢆࡶࡓࡽࡍ⤌ࡳྜ
ࢃࡏ࡟㎺ࡾ╔ࡃࡇ࡜ࡀ࠶ࡿࡓࡵࠊୡ௦ᩘࢆవ⿱ᣢࡗ࡚5000ୡ௦ࡲ࡛ィ⟬ࢆ⾜ࡗ࡚࠸ࡿࠋ
㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒࠿ࡽồࡵࡓ᭱㐺࡞⥺㟁ὶࡣ⧅ࡀࡗ࡚࠸࡞࠸≧ែ(Fig. 2)࡛࠶ࡿࡓࡵࡇࡢࡲࡲ
ࡔ࡜ᇶᯈRFࢥ࢖ࣝࡀసࢀ࡞࠸ࠋࡑࡇ࡛ࠊ⮬సࡢPython Script࡛ࡇࡢ⤌ࡳྜࢃࡏࢆ⥔ᣢࡋࡘࡘస〇ྍ⬟࡞ ᕳࡢࣃࢱ࣮ࣥ࡟ኚ᥮ࡋࡓࠋ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࢆ⾜ࡗࡓ࡜ࡁࡣヨᩱࡀxz㠃ࡢࡳᏑᅾࡍࡿ
ࡀࠊᐇ㝿ࡣy㍈᪉ྥ࡟ヨᩱࢆቑࡸࡋࡓ࡯࠺ࡀᇶᯈRFࢥ࢖ࣝࡢ☢ሙࡀ᭷ຠά⏝࡛ࡁࠊOSRࡢᨵⰋ࡟⧅ࡀࡿࠋࡑࡢࡓࡵࠊኚ᥮ࡋࡓRFࢥ࢖ࣝ ᕳࣃࢱ࣮ࣥ࡟ᑐࡋ࡚ヨᩱ㛗ࡉࢆྍኚࡍࡿ(Fig. 3)ࡇ࡜࡛
ࡉࡽ࡟OSRࢆ᭱㐺໬ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋ
OSRࢆ᭱኱࡟ࡍࡿヨᩱᙧ≧㸦┤ᚄD࡜㛗ࡉl㸧࡜ࡑࢀ࡟ᑐᛂࡍࡿᇶᯈRFࢥ࢖ࣝࢆỴࡵࡿࡓࡵ࡟ࠊ
Dࢆ2࠿ࡽ9mmࠊlࢆ20࠿ࡽ30 mmࡲ࡛ኚ໬ࡉࡏ࡚OSRࢆィ⟬ࡋࡓࠋOSRࡀ᭱኱㸦⣙0.19㸧࡟࡞ࡿ᭱㐺࡞ヨᩱࡢᙧ≧ࡣDࡀ3 mm࡛lࡀ28 mmࡢ࡜ࡁ࡛࠶ࡾࠊࡑࡢ᮲௳࡟ᑐᛂࡍࡿ᭱㐺࡞ᇶᯈRFࢥ࢖ࣝࡢᙧ≧ࡣFig. 3. ࡟♧ࡍࠋGA result

3D Calculation

D mm
z

y
x
1 mm
Gap 0.4mm

D mm

l mm
z

20 mm

y
x
1 mm

20 mm

30 mm

30 mm

Fig. 2. The optimal combination of line current

Fig. 3. The spiral planar RF coil pattern whichfrom 2000th generation of GA when sample

converted from line current and the sample

diameter D is 3 mmwith length l in 3D model for OSR calculation

ᇶᯈRFࢥ࢖ࣝࡣ㖡⟩ᇶᯈࡢFR-4 ࢆ⏝࠸࡚
LPKF c100/hfᇶᯈຍᕤᶵ࡛ຍᕤࡋࡓ(Fig. 4)ࠋヨᩱࢣ࣮ࢫ࡟ࡣෆᚄࡀ3 mmࡢࢫࢺ࣮ࣟࢆ⏝࠸
ࡓࠋᇶᯈRFࢥ࢖ࣝ⏝ࡢヨᩱᙧ≧ࡢ┤ᚄࡀ3mmࠊ㛗ࡉࡀ28 mm࡛࠶ࡿࡓࡵࠊྠヨᩱయ✚㔞
㸦2 x10-7 m3㸧࡟࡞ࡿࡼ࠺࡞᭱㐺ࢯࣞࣀ࢖ࢻRFࢥ࢖ࣝࡣ┤ᚄࡀ8.2 mmࠊ㛗ࡉࡀ6.5 mm࡛࠶ࡿࠋࢯࣞࣀ࢖ࢻRFࢥ࢖ࣝࡣࠊᕳࡁᯟࢆ3Dࣉࣜ
ࣥࢱForm3࡛〇సࡋ┤ᚄ0.4 mmࡢ㘏࣓ࢵ࢟㖡⥺ࢆᕳ࠸ࡓࠋ

Fig. 4. The spiral planar RF coil made from FR4 PCB－ 182 －

ࢩ࣑࣮ࣗࣞࢩࣙࣥ࡜ẚ㍑ࡍࡿࡓࡵࡢNMR ᐃ࡟ࡣOxford♫500 MHz NMR Magnet࡜⮬సࡢศගィࢆ⏝࠸ࡓࠋ ᐃヨᩱ࡟ࡣሷ໬࢔ࣥࣔࢽ࣒࢘NH4Cl⢊ᮎࢆ⏝࠸ࠊ14Nࡢ90ᗘࣃࣝࢫ㛗ࢆண ࡍࡿࠋᐃ᮲௳ࡣᐊ ࠊඹ㬆࿘Ἴᩘࡣ36.12 MHzࠊ✚⟬ᅇᩘࡣ4096ᅇ࡛࠶ࡿࠋܶଵ ǡ ܶଶࡢᙳ㡪ࢆ᤼㝖ࡍࡿࡓࡵ࡟ࠊᇶᯈRFࢥ࢖ࣝ࡜ࢯࣞࣀ࢖ࢻRFࢥ࢖ࣝࡢ90ᗘࣃࣝࢫ㛗ࡀྠࡌ160
s࡟࡞ࡿࡼ࠺࡟ບ㉳ࣃࣝࢫᙉᗘࢆㄪᩚࡋࡓࠋࡲࡓࠊ㔠ᒓ⌫ࡢᤄධ࡟ࡼࡿඹ᣺࿘Ἴᩘࡢኚື㔞࠿ࡽ
RFࢥ࢖ࣝࡀసࡿ☢ሙ‫ܤ‬ଵࢆ ᐃࡍࡿᡭἲ࡜ࡶẚ㍑ࡋࡓࠋ
Table. 1. The results of experiment and simulation
Experiment
Q

Power

90P(metal

90P

factor[W]ball)[us][us]

Solenoid

115.9

0.56

160.0

160

40.78

Planar coil

53.4

10

161.1

160

7.75

Coil Type

SignalSimulation

OSR

0.19

90P

Signal

[us]

[V]

155

3.06E-05

138.6

6.14E-06

OSR

0.20

⾲1࠿ࡽᐇ㦂࡜ࢩ࣑࣮ࣗࣞࢩࣙࣥࡢ⤖ᯝࡀ࡯ࡰ୍⮴ࡋ࡚࠾ࡾࠊࢩ࣑࣮ࣗࣞࢩࣙࣥࡢጇᙜᛶࡀ☜ㄆ࡛ࡁࠊ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࢆ⏝࠸ࡓRFࢥ࢖ࣝࡢ᭱㐺໬タィࡀᐇド࡛ࡁࡓࠋ㑇ఏⓗ࢔ࣝࢦࣜࢬ
࣒ࡢ᭱㐺໬࡟ࡼࡗ࡚ᇶᯈRFࢥ࢖ࣝࡢሙྜ࡛ࡶࢯࣞࣀ࢖ࢻࡢ⣙0.2ಸࡢಙྕᙉᗘࡀᚓࡽࢀࡿࠋࡓࡔ
ࡋࠊࢯࣞࣀ࢖ࢻRFࢥ࢖ࣝࡢFilling Factorࡀ0.297࡟ᑐࡋ࡚ᇶᯈRFࢥ࢖ࣝࡀ0.038㸦0.13ಸ㸧࡛࠶ࡿࡓࡵࠊྠࡌບ㉳ࣃࣝࢫᙉᗘ࡛࠶ࢀࡤᇶᯈRFࢥ࢖ࣝࡣࢯࣞࣀ࢖ࢻRFࢥ࢖ࣝ࡟ẚ࡭90ᗘࣃࣝࢫ㛗ࡀ⣙4ಸ㛗ࡃ࡞ࡿࠋ
௒ᅇࡣ⡆༢࡞┤⥺࠿ࡘ2ḟඖࡢ⥺㟁ὶࡢᇶᯈRFࢥ࢖ࣝࣔࢹࣝࢆ⤂௓ࡋࡓࡀࠊ⥺㟁ὶࢆ3ḟඖⓗ࡟㓄⨨ࡋࠊ▷࠸⥺㟁ὶࢆ⧅ࡆ࡚᭤⥺࡟౛࠼ࡿࡇ࡜ࡣྍ⬟࡛࠶ࡿࠋ౑⏝ྍ⬟࡞‫ܤ‬଴ ✵㛫ࡸヨᩱࡢܶଵ ǡ ܶଶ ࡞࡝ࡢࣃ࣓࣮ࣛࢱࢆ⪃៖ࡋࡓࣔࢹࣝࡸࠊ㏦ཷ㒊࡜ཷಙ㒊ࡀศ㞳ࡍࡿ」㞧࡞⣔࡛ࡶᑐᛂ࡛ࡁ
ࡿࠋࡲࡓࠊ㑇ఏⓗ࢔ࣝࢦࣜࢬ࣒ࡢホ౯ࣃ࣓࣮ࣛࢱࡢOSRࢆ౑࠺ࡇ࡜࡛ࢥ࢖ࣝᙧ≧ࡔࡅ࡛࡞ࡃヨᩱ✵㛫ࡢ᭱㐺໬ࡶ࡛ࡁࡿࠋ

References(1) P. Andris, I. Frollo, Optimisation of Nmr Coils By Genetic Algorithms, Meas. Sci. Rev. 2 (2002) 13–22.
(2) J.R. Hadley, C.M. Furse, D. Parker, RF coil design for MRI using a genetic algorithm, Appl. Comput.
Electromagn. Soc. J. 22 (2007) 277–286.
(3) D.I.H. Ching-Nien Chen, Biomedical Magnetic Resonance Technology, Institute of Physics Publishing, 1995
(4) O. Mallet, GALGO-2.0, (2019). https://github.com/olmallet81/GALGO-2.0.

－ 183 －

P23

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－ 185 －

P24Y

࣋ࣥࢳࢺࢵࣉ105࡟ࡼࡿ⅖⑕ᛶ⭠⑌ᝈࣔࢹ࣐ࣝ࢘ࢫࡢ࣓ࢱ࣑࣎ࣟࢡ
ࢫ◊✲‫ۑ‬ᏵᏊ㇦㸪኱す⿱Ꮨ㸪㛗⏣ㄔྖ㸪⏑Ⳁ㸪ⵓె⛥㸪⬌▱ᙪ㸪ஂ⡿⏣༤அ㸪⇃ᮌᗣ⿱㸪୰ᮧබ๎㸪⥤㒊᫬ⰾ㸪ᒣෆ୍ኵ㸪┦ἑᬛᗣ

໭ᾏ㐨኱Ꮫ኱Ꮫ㝔 ⏕࿨⛉Ꮫ㝔୰ᒣၟ஦㸦ᰴ㸧Ἀ⦖⛉Ꮫᢏ⾡኱Ꮫ㝔኱Ꮫ ᶵჾศᯒࢭࢡࢩࣙࣥ

Application of benchtop NMR for metabolomics study of Inflammatory Bowel Diseases
using DSS-induced colitis model mice‫ۑ‬Zihao Song1, Yuki Ohnishi1, Seiji Osada2, Li Gan1, Jiaxi Jiang1, Zhiyan Hu1, Hiroyuki Kumeta1, Yasuhiro
Kumaki1, Kiminori Nakamura1, Tokiyoshi Ayabe1, Kazuo Yamauchi3, Aizawa Tomoyasu1
1 Graduate School of Life Science, Hokkaido University
2 Nakayama Co.,Ltd.
3 Instrumental Analysis Section, OISTMetabolomics has shown its potential of recognizing diseases and identifying biomarkers. Indeed, highfield NMR equipped with superconducting magnet represents one of the routinely used techniques formetabolomics study. However, further application for medical purposes or field research are restricted by its
low accessibility. In this study, we applied low field, benchtop NMR (60 MHz) based on permanent magnet
to characterize the alteration of metabolic profile of feces sample obtained from the DSS-induced ulcerative
colitis model mice. Non-targeted multivariate analysis successfully discriminated the DSS-induced groupfrom the healthy control and showed high comparability with high field NMR (800 MHz). In addition, theconcentration of acetate could be accurately quantified with based on 60 MHz NMR spectra.
[Introduction] Metabolomics targets at comprehensive measurement of metabolites. It has been applied
to identify key biomarkers and investigate the pathogenesis of various human diseases. High-field NMR
spectrometer (400 MHz or higher) based on superconducting magnet has been one of the most routinely usedtechniques for metabolomics studies while further applications for medical purposes and field reseaches are
restricted because of its large size, substantial investment and requirement of cryogenic fluids maintenanceand well-trained staff. Correspondingly, the newly developed cryogen-free, low-field, benchtop NMR basedon compact permanent magnets may solve these problems and represent a new approach for metabolomics
studies for its small size and low running cost. Previous studies have detected common markers of type 2
diabetes [1-2] and tuberculosis [3] using urine sample by benchtop NMR. Nevertheless, the feasibility ofbenchtop NMR for metabolomics studies has not been universally verified and the shortcomings of low
sensitivity and resolution need to be solved. Therefore, we applied the low-field, benchtop NMR for
identifying and characterizing the metabolic profile of feces sample of DSS-induced colitis model mice.
benchtop NMR, metabolomics, feces‫ࡃࠊࢇࡆࡋ ࡇࠊࡁ࠿ ࠺ࡻࡋࠊࡾ ࢇ࠿ࠊࡌ࠸ࡏ ࡔࡉ࠾ࠊࡁ࠺ࡺ ࡋ࡟࠾࠾ࠊ࠾ࡣࡎ ࢇࡑۑ‬ࡵࡓ ࡦࢁࡺࡁࠊࡃࡲࡁ ࡸࡍࡦࢁࠊ࡞࠿ࡴࡽ ࡁࡳࡢࡾࠊ࠶ࡸ࡭ ࡜ࡁࡼࡋࠊࡸࡲ࠺ࡕ ࠿ࡎ࠾ࠊ࠶࠸ࡊࢃ ࡜ࡶࡸࡍ－ 186 －

[Method] Six mice were divided into control
group and DSS-induced group and cultivatedfor 7 days. 3.5% of DSS was added into thedrink water for DSS group mice to induce
colitis. The feces sample were collected each
day for measurement by both 800 MHz and 60
MHz NMR using water suppression pulse.
[Results] Fig. 1 shows representative 1H
NMR spectra of fecal extracts from a healthy
mouse. Comparing with 800 MHz spectra anddatabase, nineteen metabolites were annotatedFig. 1. 1H NMR spectra of mouse feces obtained by 60
MHz (up) and 800 MHz (down) spectroscopy.

on the 60 MHz spectra. Binning was exported using the total area of the spectra line of 0.04 ppm and Paretoscaling was applied. Non-targeted multivariate analysis was utilized to examine the discriminant ability ofthis model and the OPLS-DA score plot of day 2~5 was shown in Fig. 2, suggesting statistical significancefor the separation of DSS and healthy group. Importantly, it showed similar metabolic profile with 800 MHz.
Next, we quantified the concentration of acetate, which appears to be a key biomarker. The concentration of
acetate based on 60 MHz NMR spectra was quantified by curve fitting method and compared with the routine
method by using 800 MHz. No significant error was found between low field and high-field data. According
to Fig. 3, the concentration of acetate in DSS-induced group was significantly higher than the control groupat day 5. In summary, our study presented the potential benchtop NMR for the rapid diagnosis ofInflammatory bowel diseases (IBD) using DSS-induced model mice.

Fig. 2. OPLS-DA score plot of mice feces of control

Fig. 3. The concentration of acetate in the micegroup (diamond) and DSS group (circle) from day 2

fecal sample quantified by curve fitting

to day 5 acquired on 60 MHz NMR spectrometer.

method. *: p<0.05

References[1] Percival BC, et al. Low-Field, Benchtop NMR Spectroscopy as a Potential Tool for Point-of-Care Diagnosticsof Metabolic Conditions: Validation, Protocols and Computational Models. High Throughput. 2018;8(1):2.
[2] Leenders J, et al. Benchtop Low-Frequency 60 MHz NMR Analysis of Urine: A Comparative Metabolomics
Investigation. Metabolites. 2020;10(4):155.
[3] Izquierdo-Garcia JL, et al. Discovery and validation of an NMR-based metabolomic profile in urine as TB
biomarker. Sci Rep. 2020;10(1):22317.

－ 187 －

P25

ࣄࢺ㹌㹋㹐ࢹ࣮ࢱࡢࣇ࢙ࢹ࣮ࣞࢸࢵࢻ࣮ࣛࢽࣥࢢ
‫⸨ۑ‬ᮧ♩㸪ᒣ⏣㞙Ⴙ㸪⳥ᆅ῟
ᶓ὾ᕷ❧኱Ꮫ኱Ꮫ㝔࣭⏕࿨་⛉Ꮫ◊✲⛉⌮໬Ꮫ◊✲ᡤ࣭⎔ቃ㈨※⛉Ꮫࢭࣥࢱ࣮
ྡྂᒇ኱Ꮫ኱Ꮫ㝔࣭⏕࿨㎰Ꮫ◊✲⛉Federated learning using human NMR datażRei Fujimura1, Shunji Yamada2, Jun Kikuchi1, 2, 3
1

Graduate School of Medical Life Science, Yokohama City University

2

RIKEN Center for Sustainable Resource Science3

Graduate School of Bioagricultural Sciences, Nagoya University
Although NMR produces data they are compatible across institutions, it is not easy to collect medical

data from the perspective of individual personal information, and there are many preprocessing issues
involved in integrating data generated by multiple institutions in a distributed manner. Therefore, in thisstudy, we examined federated learning for human NMR data, which integrates learning models createdbased on distributed data. Preprocessing was examined to manage and utilize the distributed human NMR
data. Furthermore, we focused on lipoproteins, which are potentially involved in cardiovascular events but
are difficult to analyze due to their broad spectra, andCollected Analysis

examined the application of non-negative sparse
coding (NNSC).

Federated Analysis

Clinical Open NMR data
Add to NMR Database࠙⫼ᬒࠚClinical in-House
NMR data
Machine Learning㏆ᖺ㸪ᐇ㦂⛉Ꮫࡸ⌮ㄽ⛉Ꮫ࡜࡞ࡽࡪ᪂ࡓ࡞⛉Ꮫ࡛

Data Linking andFormat Unification࠶ࡿࢹ࣮ࢱࢧ࢖࢚ࣥࢫࡀὀ┠ࢆᾎࡧ࡚࠸ࡿ㸬⑓㝔ࡸྛ◊✲ᶵ㛵࡟࡚཰㞟ࡉࢀࡓ་⒪ࢹ࣮ࢱࡢά⏝ࡀ

Aggregated Databaseᮇᚅࡉࢀ࡚࠸ࡿ㸬NMRࡣ㸪⡆᫆࡞ࢧࣥࣉࣝ‽ഛ࡛ΰྜ≀ࡢ⤌ᡂࢆホ౯࡛ࡁ㸪ᶵ㛵㛫஫᥮ᛶࡢ࠶ࡿ

Local Model

Data Preprocessing

Federated
Learning

Machine Learning
Meta-Analysis

Global Modelࢹ࣮ࢱࢆ⏕ᡂ࡛ࡁࡿ㸬ࡋ࠿ࡋ㸪ࣄࢺNMRࢹ࣮ࢱࡢ཰㞟ࡣಶே᝟ሗಖㆤࡢほⅬ࡛ᐜ࡛᫆ࡣ࡞࠸㸬ࡲࡓ㸪ከᶵ㛵࡛ ᐃࡉࢀࡓࢹ࣮ࢱࡢ⤫ྜ࡟࠶ࡓࡗ࡚
ࡢ๓ฎ⌮࡟࠾࠸࡚ࡶㄢ㢟ࡀ࠶ࡿ[1]㸬ᮏ◊✲࡛

Fig.1. Conceptual diagram of collected andࡣ㸪ศᩓᆺࡢࣄࢺNMRࢹ࣮ࢱࡢ⟶⌮࣭ά⏝࡟ྥfederated analysis for human NMR data.

ࡅ࡚ࡢ๓ฎ⌮ࢆ⾜࠺[2]㸬ࡲࡓ㸪ࢹ࣮ࢱࡑࡢࡶࡢ

Left: collected analysis. Right: federated analysis.

ࢆ཰㞟ࡍࡿࡢ࡛ࡣ࡞ࡃ㸪ศᩓⓗ࡟⟶⌮ࡉࢀࡓࢹ࣮ࢱࢆࡶ࡜࡟సࡽࢀࡓᏛ⩦ࣔࢹࣝࢆ⤫ྜࡍࡿࣇ࢙
ࢹ࣮ࣞࢸࢵࢻ࣮ࣛࢽࣥࢢࢆࣄࢺNMRࢹ࣮ࢱ࡟࠾࠸᳨࡚ウࡍࡿ(Fig.1)[3]㸬NMR࡟ࡼࡾᚰ⾑⟶࢖࣋ࣥࢺ࡟㛵୚ࡋ࡚࠸ࡿ࣏ࣜࢱࣥࣃࢡ㉁࡟ὀ┠ࡋࡓ◊✲ࡀ⾜ࢃࢀ࡚࠸ࡿࡀ㸪ࢫ࣌ࢡࢺࣝࡀࣈ࣮ࣟࢻ࡟
࡞ࡾ㸪ゎᯒࡀᅔ㞴࡛࠶ࡿ[4]㸬ࡑࡇ࡛㸪ࣈ࣮ࣟࢻ࡞ࢫ࣌ࢡࢺࣝ࡟ᑐࡋ࡚ࣆ࣮ࢡศ㞳ἲNon-negative
sparse coding (NNSC)ࡢ㐺⏝ࢆ᳨ウࡍࡿ[5]㸬ྛࢫ࣌ࢡࢺࣝࡢ≉ᚩ࡙ࡅࡸ⑌ᝈ࡜ࡢ㛵㐃ᛶ㸪እⓗせᅉ࡟ࡼࡿ೺ᗣ≧ែࡢኚ໬ࢆᤊ࠼ࡿ㸬㉸ศᏊ」ྜయ㸪ᶵ㛵㛫஫᥮ᛶ㸪ศᩓᆺࢹ࣮ࢱά⏝‫࠸ࢀࡽࡴࡌࡩۑ‬㸪ࡸࡲࡔࡋࡹࢇࡌ㸪ࡁࡃࡕࡌࡹࢇ

－ 188 －

࠙᪉ἲࠚCollected Analysis࡜ࡋ࡚㸪NMRࡢ࣮࢜ࣉࣥࢹ

Data Integration Approach࣮ࢱ࣮࣋ࢫ࡛࠶ࡿMETABOLOMICS

Peak Separationin Lipoprotein Spectra

Data
Preprocessing

WORKBENCH[6]㸪MetaboLights[7]࡟࡚ࣄࢺ⾑₢NMRࢹ࣮ࢱࢭࢵࢺࢆ1ࡘࡎࡘ཰㞟ࡋࡓ㸬
NMRࣃ࣓࣮ࣛࢱ(ACQUSࣇ࢓࢖ࣝ)࠿ࡽ㸪☢ሙ

¼ Magnetic field strength¼ Data pointᙉᗘ㸪ࢫ࣌ࢡࢺࣝᖜ㸪✚⟬ᅇᩘ㸪࣏࢖ࣥࢺᩘ

Zero
Fillingࢆ☜ㄆࡋᙜࣛ࣎ෆࢹ࣮ࢱ[8]࡜㛵㐃ࡢ࠶ࡿࢹ࣮

Fourier
Transform另 Magnetic field strength另 Data point

Phase
Correction

Baseline
Correction

NNSCࢱࢆ㑅ᐃࡋࡓ㸬␗࡞ࡿNMRࣃ࣓࣮ࣛࢱࢆᣢࡘ

Fig. 2. NMR data integration approach.

ࢹ࣮ࢱࢆ⤫ྜࡍࡿࡓࡵ࡟㸪Pythonࡢnmrglueࢆ

Top: Integrated approach for NMR data acquired⏝࠸࡚࢔࣏ࢲ࢖ࢮ࣮ࢩࣙࣥ࡞࡝ࡢ๓ฎ⌮ࡢ᳨with different parameters. Bottom: Flow of theウࢆ⾜࠸(Fig.2)㸪NNSCࢆ㐺⏝ࡋࡓࠋࣆ࣮ࢡศ

process including preprocessing.

㞳ࡋࡓᡂศ࡟ᑐࡋࠊ࢔ࣀࢸ࣮ࢩࣙࣥࢆ⾜ࡗࡓࠋసᡂࡋࡓࢹ࣮ࢱࢭࢵࢺ࡟ᑐࡋ࡚㸪┠ⓗኚᩘࢆ⑕≧ࡢ᭷↓࡜ࡋ㸪ࣛࣥࢲ࣒ࣇ࢛ࣞࢫࢺゎᯒࢆ⾜ࡗࡓ㸬࠙⤖ᯝ࣭⪃ᐹࠚ
࣮࢜ࣉࣥࢹ࣮ࢱ࣮࣋ࢫ࠾ࡼࡧࣛ࣎ෆ࠿ࡽ཰㞟ࡋࡓ10ಶࡢࣄࢺ⾑₢NMRࢹ࣮ࢱࢭࢵࢺ࡟ࡘ࠸࡚ࠊ
☢ሙᙉᗘࡸ࣏࢖ࣥࢺᩘࢆጞࡵ࡜ࡋࡓNMRࣃ࣓࣮ࣛࢱࢆACQUSࣇ࢓࢖ࣝ࠿ࡽㄞࡳྲྀࡾ[9]ࠊࣃ࣓ࣛ
࣮ࢱࢆࣜࢫࢺ໬ࡋࡓࠋᙜࣛ࣎ࡀᡤ᭷ࡍࡿ៏ᛶ⑂ປᝈ⪅࡜ᑐ↷⿕㦂⪅࡟࠾ࡅࡿ1H NMRࢫ࣌ࢡࢺࣝ
࡟ࡘ࠸࡚㸪࣏ࣜࢱࣥࣃࢡ㉁㡿ᇦࡢࣆ࣮ࢡศ㞳ࢆ⾜࠸㸪ࣛࣥࢲ࣒ࣇ࢛ࣞࢫࢺࢆ⏝࠸࡚⑌ᝈࡢ᭷↓࡟࠾ࡅࡿ㔜せᅉᏊࢆ᥈⣴ࡋࡓ(Fig.3)㸬VLDLࡣᝈ⪅࡜ᑐ↷ࢆุูࡍࡿࡢ࡟᭱ࡶ㔜せ࡛࠶ࡗࡓ㸬ࡇࡢ⤖ᯝࡣ㸪௨๓࡟ሗ࿌ࡉࢀࡓྍኚ㔜せᗘศᯒࡢ⤖ᯝࡀ୍⮴ࡋ࡚࠸ࡓ㸬⢭ᗘࡢ᳨ドࡢࡓࡵ㸪㐣Ꮫ⩦㸪ỗ໬ᛶ⬟㸪஺ᕪ᳨ド㸪ࣁ࢖ࣃ࣮ࣃ࣓࣮ࣛࢱࡢ

(a)᭱㐺໬࡟ࡘ࠸᳨࡚ウࡍࡿ㸬ࡲࡓ㸪Federated

(b)
VLDL

LDL

HDL

Learningࢆ⾜࠺ࡓࡵ࡟㸪ศᩓᆺࡢࢹ࣮ࢱ࡟ᑐ
ࡋᶵᲔᏛ⩦ࢆ⾜࠸㸪࣮ࣟ࢝ࣝࣔࢹࣝࢆస〇ࡋ㸪」ᩘࡢ࣮ࣟ࢝ࣝࣔࢹࣝ࡟ᑐࡋᶵᲔᏛ⩦ࢆ⾜࠺஦࡛ࢢ࣮ࣟࣂࣝࣔࢹࣝࢆస〇ࡍࡿ㸬

Fig. 3. Searching for key factors in disease by

Collected Analysis࡜Federated Analysis࡛ࡑࢀࡒࢀసᡂࡉࢀࡓᏛ⩦ࣔࢹࣝࡢᛶ⬟ࢆẚ㍑ࡍࡿ
ࡇ࡜࡛㸪Federated Analysisࡢ᭷⏝ᛶࢆ᳨ウࡍࡿ㸬௒ᚋ㸪Collected Analysisࡢ๓ฎ⌮㸪random forest using lipoprotein NMR spectra(a) Importance factors extracted by random forest.
(b) Peak separation of lipoprotein spectrum.

Federated Analysisࡢ᳨ウࢆ┠ᣦࡍ㸬
References[1] Schober. D., et al., Anal. Chem, 90, 649-656, 2018. [2] Buendia, P., et al., Bioanalysis, 11, 1139-1155,
2019. [3] Tedeschini, BC., et al., IEEE Access. 10, 8693-8708 2022. [4] Masuda, R., et al., Anal Chem, 94,
4426-4436, 2022. [5] Yamada, S., et al., ACS Omega, 4, 2261-2269, 2019. [6] Sud, M., et al., Nucleic Acids
Res., 44, D463–D470. [7] Huag, K., et al., Nucleic Acids Res., 48, D440-D444, 2020. [8] Kitami, T. et al.,Sci. Rep. 10, 1-12 (2020). [9] Hara, K., et al., Processes 10, 1264(2022).

－ 189 －P26Y

14

N NMR࡟࠾ࡅࡿ☢ሙ౫Ꮡᛶ: 㧗☢ሙࡢ᪉ࡀ᭷฼࠿㸽‫ۑ‬㨶㏉♸ኴᮁ㸪すᒣ⿱௓1,2
1,2 JEOL RESONANCEࠊRIKEN-JEOL㐃ᦠࢭࣥࢱ࣮

B0 field dependence of 14N NMR: Higher the better?
‫ۑ‬Yutaro Ogaeri1,2, Yusuke Nishiyama1,2
1,2

JEOL RESONANCE, RIKEN-JEOL Collaboration Center
It is recently shown that 1H-14N overtone (OT)-RESPDOR efficiently probes 1H-14N spatial proximities.

Despite the common believe that higher B0 field is beneficial to NMR, it is not clear whether high B0 field
is preferable to 14N OT, since the OT nutation frequency is inversely proportional to B0 field. In this study,
we performed 1H-14N OT-RESPDOR experiments at several different magnetic fields and clarified the B0
field dependence of the detection efficiency. Experimental results showed that the detection efficiency of1

H-14N OT-RESPDOR is independent of the B0 field strength and size of quadrupolar coupling, provided

the 14N OT pulse lengths are optimized.
ࠚ࠙⫼ᬒࠚ❅⣲ཎᏊࡣࠊᵝࠎ࡞ศ㔝࡟࠾࠸࡚㔜せ࡞ඖ⣲࡛࠶ࡿࡀࠊࡑࡢNMR ᐃࡣ୍➽⦖࡟ࡣ࠸࠿࡞
࠸ࠋ❅⣲ཎᏊ࡟ࡣ14N࡜15Nࡢ஧✀㢮ࡢNMR࢔ࢡࢸ࢕ࣈ࡞᰾ࡀᏑᅾࡍࡿࡀࠊ15Nࡢኳ↛Ꮡᅾẚࡣ1%௨ୗ࡛࠶ࡾࠊኳ↛Ꮡᅾẚ࡛ࡢほࡣ㛗᫬㛫ࡢ✚⟬ࢆᚲせ࡜ࡍࡿࠋࡑࢀ࡟ᑐࡋࠊ14Nࡣ99%௨ୖࡢኳ↛ᏑᅾẚࢆᣢࡘࡶࡢࡢࠊᅄᴟᏊ┦஫స⏝ࢆᣢࡘᩚᩘࢫࣆࣥ(I = 1)࡛࠶ࡿࡓࡵ┤᥋

ᐃࡣᅔ㞴࡛

1

࠶ࡗࡓࠋࡋ࠿ࡋ࡞ࡀࡽࠊ㧗㏿ࡢヨᩱᅇ㌿ࡢࡶ࡜࡛ H࡟ࡼࡿ㛫᥋ ᐃࢆ⏝࠸ࡿࡇ࡜࡛ࠊᩘศ⛬ᗘ࡛ࡢ㧗ឤᗘ ᐃࡀᐇ⌧ࡋࡓࠋ㏆ᖺࠊLarmor࿘Ἴᩘࡢ2ಸࡢ࿘Ἴᩘࢆ⏝࠸ࡓ14N overtone (OT)RESPDOR NMR1࡟ࡼࡾ㛗㊥㞳ࡢ┦㛵ಙྕࢆ㧗ឤᗘ࡛ ᐃ࡛ࡁࡿࡇ࡜ࡀሗ࿌ࡉࢀࡓࠋ୍⯡ⓗ࡟㧗☢ሙࡀឤᗘ࣭ศゎ⬟ࡢ㠃࡛᭷฼࡛࠶ࡿ࡜ゝࢃࢀ࡚࠸ࡿࡢ࡟ᑐࡋ࡚ࠊ☢ሙᙉᗘࡢຠᯝࡣ14N OT࡟࠾࠸࡚ࡣ᫂☜࡛ࡣ࡞࠸ࠋࡇࢀࡣࠊ㧗☢ሙ࡟࠾࠸࡚ࡣ14N OTࡢnutation frequencyࡀ࠿࠼ࡗ࡚పࡃ࡞ࡿ
ࡓࡵ࡛࠶ࡿࠋ࡛ࡣప☢ሙࡢ᪉ࡀⰋ࠸࠿࡜࠸࠼ࡤࠊ⥺ᖜࡀᗈࡃ࡞ࡿࡓࡵࠊឤᗘࡢపୗ࡟ࡘ࡞ࡀࡿྍ
⬟ᛶࡀ࠶ࡿࠋᮏ◊✲࡛ࡣ」ᩘࡢ␗࡞ࡿᙉࡉࡢ☢ሙ࡟࠾࠸࡚1H-14N OT-RESPDORࡢᐇ㦂ࢆ⾜࠸ࠊ᳨ฟຠ⋡ࡢ☢ሙ౫Ꮡᛶࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋࡓࠋ࠙ࣃࣝࢫࢩ࣮ࢣࣥࢫࠚ
Fig.1࡟1H-14N OT-RESPDORࡢࣃࣝࢫࢩ࣮ࢣࣥࢫࢆ♧ࡍࠋ1H-14Nࡢ཮ᴟᏊ┦஫స⏝ࡀSR4ࢩ࣮ࢣࣥࢫ࡟ࡼࡾᅇ᚟
ࡉࢀࡿࡀࠊ1HࡢSࣃࣝࢫ࡟ࡼࡗ࡚ࣜࣇ࢛࣮࢝ࢫࡍࡿࠋࡇࡢ
ཧ↷ࢩࢢࢼࣝࢆS0࡜ࡍࡿࠋ୍᪉࡛ࠊ஧ࡘࡢSR4ࣜ࢝ࢵࣉࣜ
ࣥࢢࣈࣟࢵࢡࡢ㛫࡛14Nࡢඹ㬆࿘Ἴᩘࡢ஧ಸ (OT) ࡢࣃࣝࢫࢆᡴࡘࡇ࡜࡟ࡼࡾࠊ཮ᴟᏊ┦஫స⏝ࡢࣜࣇ࢛࣮࢝ࢫࢆጉ
ࡆࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡇࡢࢩࢢࢼࣝࢆS’࡜ࡍࡿࠋ14Nࡢ㏆ഐ࡟
࠶ࡿ1HࡢಙྕࡣS0࡜S’ࡢᕪ࡜ࡋ࡚⌧ࢀࡿࠋࡇࡢS0-S’ࢫ࣌ࢡࢺࣝࢆᵝࠎ࡞14N OT࢜ࣇࢭࢵࢺ࡟ᛂࡌ࡚ࣉࣟࢵࢺࡍࡿࡇ࡜
࡛ࠊ1H-14N┦㛵ࢫ࣌ࢡࢺࣝࡀᚓࡽࢀࡿࠋ
㧗㏿MAS, 14N NMR‫ࡅࡍ࠺ࡺࡲࡸࡋ࡟ࠊ࠺ࢁࡓ࠺ࡺࡾ࠼ࡀ࠾ۑ‬－ 190 －

Fig.1 pulse sequence of 1H-14N OT-RESPDOR

Signal is recorded with(S’)/without(S0) the 14N
saturation pulse.

࠙⤖ᯝࠚ
14

(A)

9.4࠾ࡼࡧ14.1, 16.5, 21.1 Tࡢྛ☢ሙ࡟࠾࠸࡚ࠊᵝࠎ࡞ N OTࣃࣝࢫࡢ㛗ࡉ࡛14N OT RESPDOR ᐃࢆ⾜࠸ࠊྛ☢ሙ࡟࠾ࡅࡿ᳨ฟຠ⋡ࡀ᭱኱࡜࡞
ࡿ14N OTࣃࣝࢫᖜ࠾ࡼࡧࡑࡢ᫬ࡢ᳨ฟຠ⋡ࢆồࡵࡓࠋẚ㍑ࡢࡓࡵ࡟ࠊྛ
☢ሙ࡟࠾࠸࡚ྠࡌ14N OT B1ᙉᗘࢆ⏝࠸ࡓࠋࢧࣥࣉࣝࡣࠊN-Acetyl Alanine(CQ(NH) = 3.4 MHz, CQࡣᅄᴟᏊ࢝ࢵࣉࣜࣥࢢᐃᩘ) (Fig.2 A) ࢆ⏝࠸ࡓࠋࡑ(B)ࡢ⤖ᯝࠊ☢ሙࢆ኱ࡁࡃࡍࡿ࡯࡝᳨ฟຠ⋡ࡀ᭱኱࡜࡞ࡿ14N OTࣃࣝࢫᖜࡀ
㛗ࡃ࡞ࡿࡇ࡜ (Fig.3) ࠊ᭱኱᳨ฟຠ⋡ࡣ࡝ࡢ☢ሙ࡟࠾࠸࡚ࡶ1Hࢫࣆ࢚ࣥࢥ
࣮ಙྕࡢ10%๓ᚋ࡟࡞ࡿ࡜࠸࠺ࡇ࡜ࡀศ࠿ࡗࡓ (Fig.4)ࠋ
ḟ࡟ࠊN-Acetyl Alanine࡜ࡣ␗࡞ࡿ኱ࡁࡉࡢᅄᴟᏊࢆᣢࡘ❅⣲ཎᏊࢆྵ Fig.2 Chemical structure of Nࡴorthorhombic L-Histidine (CQ(NH) = 1.8 MHzࠊCQ(NH3+) = 1.2 MHz) (Fig.2 Acetyl Alanine (A) andB) ࢆ⏝࠸࡚ࠊN-Acetyl Alanine࡜ྠᵝࡢᐇ㦂࡟ࡼࡾ᳨ฟຠ⋡ࢆồࡵࠊẚ㍑ orthorhombic L-Histidine (B)ࡋࡓࠋࡑࡢ⤖ᯝࠊL-HistidineࡢNHࢩࢢࢼࣝ࠾ࡼࡧNH3+ࢩࢢࢼࣝࡢ
୧᪉࡟ࡘ࠸࡚ࡶ᳨ฟຠ⋡ࡣ☢ሙࡢ኱ࡁࡉ࡟ࡼࡗ࡚ኚ໬ࡏࡎࠊ10%๓ᚋࡢ᳨ฟຠ⋡ࢆ♧ࡋࡓ (Fig.4)ࠋ
࠙⪃ᐹࠚ
ࠚ
14

N OTࡢບ㉳ࡣḟࡢᅄᴟᏊ┦஫స⏝࡟ࡼࡗ࡚㉳ࡇࡿࡓࡵࠊ
nutation frequencyࡣCQ2/Z ࡟ẚ౛ࡍࡿࠋࡍ࡞ࢃࡕప☢ሙ࡟࠾࠸࡚ࠊ
࠶ࡿ࠸ࡣ኱ࡁ࡞ᅄᴟᏊࢆᣢࡘ14NཎᏊ࡟࠾࠸࡚nutation frequencyࡀ㧗ࡃ࡞ࡿࠋᐇ㝿࡟Fig.3࡟ࡳࡽࢀࡿࡼ࠺࡟ྠࡌB1ᙉᗘ࡛ࡶప☢ሙ࡛ࡣ▷࠸ࣃࣝࢫ࡛᭱኱ᙉᗘࡀᚓࡽࢀ࡚࠸ࡿࠋ୍᪉࡛14N OT⥺ᖜࡣࠊ
CQ2/Z ࡟ẚ౛ࡍࡿ஧ḟࡢຠᯝ࡟ẚ౛ࡍࡿࠋ14N OTࣃࣝࢫࡢບ㉳⠊ᅖࡣ⊃ࡃࠊప☢ሙ࠶ࡿ࠸ࡣ኱ࡁ࡞ᅄᴟᏊࡢࡶࡓࡽࡍᗈ࠸⥺ᖜࡢࡍ࡭࡚ࢆບ㉳࡛ࡁࡎឤᗘࡀపୗࡍࡿྍ⬟ᛶࡀ࠶ࡿࠋࡋ࠿ࡋ࡞ࡀࡽᐇ
㦂⤖ᯝࡣࡇࡢྍ⬟ࢆྰᐃࡋ࡚࠾ࡾࠊບ㉳ຠ⋡ࡢ☢ሙ࣭ᅄᴟᏊ
ࡉࢀ࡞࠿ࡗࡓࠋヲ⣽࡞ゎᯒࢆ⾜࠺ Fig.3 Relation of NH signal intensity of N-Acetyl
14࡜ࠊ࠸ࡎࢀࡢሙྜ࡟࠾࠸࡚ࡶSR4ࣜ࢝ࢵࣉࣜࣥࢢ࡟ࡼࡾಙྕ Alanine and pulse widths of N OT pulse.
ࡢ኱ࡁࡉ࡟ࡼࡿຠᯝࡣほ14
ᙉᗘࡀ1/2࡟࡞ࡾࠊ14N OT-RESPDOR࡟ࡼࡾࡉࡽ࡟1/5ࠊ⥲ィ࡛ Intensity of NH signal with each N OT pulse

width is arrayed. Intensity of the maximum
10%ࡢಙྕࡢࡳࡀṧࡗ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ
௨ୖࡢ㆟ㄽࡼࡾࠊ⇕ᖹ⾮☢໬࡟ᑐࡋ࡚ࡢ14N OT-RESPDOR efficiency of each B0 field is marked in red.
ࡢບ㉳ຠ⋡ࡣ☢ሙ࣭ᅄᴟᏊ࡟౫Ꮡࡋ࡞࠸ࡇ࡜ࡀศ࠿ࡗࡓࠋ
ࡶࡗ࡜ࡶࠊ㧗☢ሙ࡛ࡣ⇕ᖹ⾮☢໬ࡀ኱ࡁࡃ࡞ࡿ࡜࠸࠺Ⅼ࠾ࡼࡧ⥺ᖜࡀ⣽ࡃ࡞ࡿ࡜࠸࠺Ⅼ࡟࠾࠸࡚ᮃࡲࡋ࠸ࠋ
Fig.4 filtering efficiency of 1H-14N OT-RESPDOR

The filtering efficiency of each nitrogen atom
/ B0 field is shown. Blue: Histidine NH3+
(1.2 MHz) Red: Histidine NH (1.8 MHz)Green: N-Acetyl Alanine (3.4 MHz)N

References

1. Duong, N. T. & Nishiyama, Y. Detection of remote proton-nitrogen correlations by
1H-detected 14N overtone solid-state NMR at fast MAS. Physical Chemistry Chemical
Physics (2022) doi:10.1039/d2cp00155a.

－ 191 －

P27

ከ᰾ᅛయNMRࢆ⏝࠸ࡓ㧗⅔ࢭ࣓ࣥࢺ୰ᛶ໬ᣲືࡢゎᯒ‫ۑ‬㧗ᶫ㈗ᩥ㸪ㅖᒸ ➼኱ሯຬ௓
᪥ᮏ〇㕲ᰴᘧ఍♫᪥㕲㧗⅔ࢭ࣓ࣥࢺᰴᘧ఍♫

Multi-nuclear solid state NMR analysis on carbonation behavior of blast furnace slag
cementżTakafumi Takahashi1, Hitoshi Morooka1, Yusuke Otsuka2
1

Nippon Steel Corporation

2 Nippon Steel Blast Furnace Slag Cement Co., Ltd.

Using Ground blast furnace slag (GGBS) cement can save energy consumption and decrease the amountof CO2 emission since a part of clinker of BFS cement is substituted by fine particles of BFS that has been
produced in an iron making process. Based on the estimation under accelerated condition, one of thedisadvantages of BFS cement is considered to be low durability against carbonation. Recent findings,
however, suggest that carbonation under accelerated condition would not adequately follow reaction underreal atmospheric one. In this study, chemical structural changes of BFS cement under atmospheric andaccelerated condition were investigated by using multi-nuclear solid state NMR. It was found thatcarbonation under accelerated condition could deteriorate the property of BFS cement more than that in
atmospheric condition.
1.

⥴ゝ㧗⅔ࢭ࣓ࣥࢺࡣࠊ㧗⅔Ỉ○ࢫࣛࢢࢆ⢊○ࡋ࡚ᚓࡽࢀࡓ㧗⅔ࢫࣛࢢᚤ⢊ᮎ࡜ࠊᬑ㏻࣏ࣝࢺࣛࣥࢻ

ࢭ࣓ࣥࢺࢆΰྜࡋ࡚〇㐀ࡉࢀࡿࠋࡇࡢ〇㐀᪉ἲ࡟ࡼࡗ࡚ࠊཎᩱ࠾ࡼࡧ࢚ࢿࣝࢠ࣮ࡢᾘ㈝ࡀᢚ࠼ࡽ
ࢀࠊ▼⅊▼ࡢ⇕ศゎ➼࡟㉳ᅉࡍࡿCO2ࡢ᤼ฟ㔞ࡶᢚไࡉࢀࡿࡓࡵࠊ㧗⅔ࢭ࣓ࣥࢺࡣ┬CO2࣭┬࢚ࢿ࡟㈨ࡍࡿᮦᩱ࡜ᤊ࠼ࡽࢀ࡚࠸ࡿࠋࡲࡓࠊࡑࡢ໬Ꮫⓗ᢬ᢠᛶࡢ㧗ࡉࠊ࢔ࣝ࢝ࣜࢩࣜ࢝཯ᛂᢚไຠᯝ
࠾ࡼࡧ㛗ᮇᙉᗘࡢቑ㐍➼ࡢ㛗ᡤࢆά࠿ࡋࠊᅵᮌᕤ஦ࠊᘓ⠏ᇶ♏➼࡟౑⏝ࡉࢀ࡚࠾ࡾࠊ௒ᚋࡶሀㄪ࡞㟂せࡀᮇᚅࡉࢀࡿࠋ୍᪉࡛ࠊ㧗⅔ࢭ࣓ࣥࢺࡣᬑ㏻࣏ࣝࢺࣛࣥࢻࢭ࣓ࣥࢺ࡟ẚ࡭࡚୰ᛶ໬㏿ᗘࡀ
㏿ࡃࠊ኱Ẽ⎔ቃୗ࡛ࡢ⪏ஂᛶ࡟ຎࡿ࡜ࡉࢀ࡚ࡁࡓࠋ㏆ᖺࠊ౪⏝ᮇ㛫87ᖺࡢࢥࣥࢡ࣮ࣜࢺᵓ㐀≀ࡢ㗰ᮦ⭉㣗࡟㛵ࡍࡿㄪᰝࡀ⾜ࢃࢀࡓ⤖ᯝࠊ㗰ᮦ⭉㣗࡬ࡢᙳ㡪ࡣ୰ᛶ໬ࡼࡾỈࡢᾐ㏱ࡢᙳ㡪ࡀ኱ࡁ࠸ࡇ࡜ࡀุ᫂ࡋࠊ㧗⅔ࢭ࣓ࣥࢺࡢ⪏ஂᛶホ౯ࡢぢ┤ࡋࡀ㆟ㄽࡉࢀ࡚࠸ࡿ1ࠋࡉࡽ࡟ࠊ㧗⅔ࢭ࣓ࣥࢺ࡟
㛵ࡋ࡚ࡣࠊ⪏ஂᛶホ౯ࡢࡓࡵࡢಁ㐍⎔ቃヨ㦂ࡀࠊᐇ㝿ࡢ኱Ẽ⎔ቃୗ࡛ࡢ୰ᛶ໬࡜ࡣ␗࡞ࡿྍ⬟ᛶࡶᣦ᦬ࡉࢀ࡚࠾ࡾ2ࠊᐇయࡢゎ᫂ࡀᚲせ࡜ࡉࢀ࡚࠸ࡿࠋ௨ୖࡢⅬࢆ㋃ࡲ࠼ࠊᮏ◊✲࡛ࡣࠊ୰ᛶ໬ヨ㦂᮲௳ࡀ໬Ꮫᵓ㐀࡟୚࠼ࡿᙳ㡪ࢆ᳨ドࡍࡿࡓࡵࠊಁ㐍⎔ቃୗ࠾ࡼࡧ኱Ẽ⎔ቃୗ࡛୰ᛶ໬ฎ⌮ࢆ⾜ࡗࡓ㧗⅔ࢭ࣓ࣥࢺ◳໬య࡟ࡘ࠸࡚ࠊከ᰾ᅛయNMRἲ࡟ࡼࡿ໬Ꮫᵓ㐀ゎᯒࢆᐇ᪋ࡋࡓࠋ
2.

ᐇ㦂᪉ἲ
㧗⅔ࢭ࣓ࣥࢺࡣࠊ◊✲⏝࣏ࣝࢺࣛࣥࢻࢭ࣓ࣥࢺ࡟ᑐࡋ㧗⅔ࢫࣛࢢᚤ⢊ᮎࢆ85mass%ῧຍ࣭ΰྜ

ࡋ࡚స〇ࡋࡓࠋヨᩱࡢ໬Ꮫ⤌ᡂࢆTable 1࡟♧ࡍࠋୖグ㧗⅔ࢭ࣓ࣥࢺ࡜ỈࢆỈ㸭ᅛẚ=60%࡛ΰྜࡋࡓᚋࠊ20Υ࣭7᪥㛫ᑒ⥸㣴⏕㸦ࢧ࢖ࢬ㸸5mm10mm50mm㸧ࡋࡓࠋࡑࡢᚋࠊᑒ⥸㣴⏕ヨᩱࢆࠊᐊෆ㸦኱Ẽ㸧⎔ቃ㸦20ႏ, 60㸣RH, 0.04%CO2㸧࠾ࡼࡧಁ㐍⎔ቃ㸦20ႏ, 60㸣RH, 5.0%CO2㸧࡛ࠊࡑࢀࡒ
ࢀ100%୰ᛶ໬ฎ⌮ࡋࡓࠋ୰ᛶ໬᏶஢᫬ᮇࡣࠊࣇ࢙ࣀ࣮ࣝࣇࢱࣞ࢖ࣥᾮᰁⰍἲ࡟ࡼࡾ◳໬యෆ㒊ࡀከ᰾ᅛయ NMRࠊ㧗⅔ࢭ࣓ࣥࢺࠊ୰ᛶ໬
ࠐࡓ࠿ࡣࡋ ࡓ࠿ࡩࡳࠊࡶࢁ࠾࠿ ࡦ࡜ࡋࠊ࠾࠾ࡘ࠿ ࡺ࠺ࡍࡅ－ 192 －

╔Ⰽࡉࢀ࡞࠸ࡇ࡜ࢆ᰿ᣐ࡟ุ᩿ࡋࠊ࢔ࢭࢺࣥࢆ⏝࠸ࡓD-Dryἲ࡟ࡼࡾỈ࿴೵Ṇࡋࠊศᯒヨᩱ࡜ࡋࡓࠋ
࡞࠾ࠊ୰ᛶ໬᏶஢ᮦ㱋ࡣࠊᐊෆ⎔ቃ㸸14᪥ࠊಁ㐍⎔ቃ㸸7᪥࡛࠶ࡗࡓࠋ
Table 1. Chemical composition of blast furnace cement (BFS) pastes.
Chemical composition [mass䠂]Na2O K2O
TiO2
SO3

SiO2

Al2O3

Fe2O3

CaO

MgO

B85

30.97

12.66

0.78

47.41

4.84

2.1.

ᅛయNMR ᐃ29Si MAS

2.1.1.

2.02

0.52

࠾ࡼࡧ 29Si{1H}CPMAS ࢫ࣌ࢡࢺࣝ

29

ᅛయ Si MAS NMRࢫ࣌ࢡࢺࣝ

0.16

0.26

P2O5

MnO

Cl

ig.loss

0.28

0.02

0.003

0.28

ᐃ

1

ᐃࡣࠊ㟼☢ሙ9.4T( H ඹ㬆࿘Ἴᩘ400.265MHzࠊ29Si ඹ㬆࿘Ἴᩘ

79.521MHz) JEOL-ECA400ศගィࢆ⏝࠸࡚ᐇ᪋ࡋࡓࠋ஧㔜ඹ㬆8 mmĳࣉ࣮ࣟࣈࢆ⏝࠸ࠊᅇ㌿࿘Ἴᩘ7kHz, ࣃࣝࢫᖜ 1.09ȝs (18oࣃࣝࢫ)ࠊ⦆࿴᫬㛫ࢆ⪃៖ࡋࠊ⧞ࡾ㏉ࡋ᫬㛫 9 sࠊ✚⟬ᅇᩘ10000ᅇ࡜
ࡋࡓࠋ29Si{1H} CPMASࢫ࣌ࢡࢺࣝ ᐃࡶୖグ࡜ྠᵝࡢ☢ሙࠊᅇ㌿ᩘࢆ⏝࠸࡚ᐇ᪋ࡋࡓࠋ1H ࡢ90oࣃࣝࢫᖜ 5.1ȝs, ⧞ࡾ㏉ࡋ᫬㛫5sࠊ✚⟬ᅇᩘ28000ᅇࠊcontact time 0.2 ms,࡜ࡋࠊHartmann-Hahn᮲௳ࢆ‶ࡓࡍࡼ࠺RFᙉᗘࢆタᐃࡋࡓࠋ
27Al MAS & 3QMAS NMRࢫࢫ࣌ࢡࢺࣝ

2.1.2.

27Al MAS NMRࢫ࣌ࢡࢺࣝ

ᐃᐃࡣࠊ㟼☢ሙ16.4T(27Alඹ㬆࿘Ἴᩘ182.24 MHz)ࡢୗ࡛ࠊJEOL-ECA700ศගィࠊ4mmĳ3QMASࣉ࣮ࣟࣈࢆ⏝࠸࡚ᐇ᪋ࡋࡓࠋ඲࡚ࡢ
27Al MASࢫ࣌ࢡࢺࣝࢆ

ࡋࡓࠋᐃ࡟ࡘ࠸࡚ࠊᅇ㌿࿘Ἴᩘࡣ18 kHz࡜ᐃࡍࡿ㝿࡟ࡣࠊᐃ㔞ᛶࢆ☜ಖࡍࡿࡓࡵࠊࣃࣝࢫᖜ1 ȝs㸦18oࣃࣝࢫ㸧ࠊ

⧞ࡾ㏉ࡋ᫬㛫ࢆ 3 s࡜ࡋࠊ6400ᅇࡢ✚⟬ࢆᐇ᪋ࡋࡓࠋ3QMAS ᐃࡣࠊDQF-SPAMࢩ࣮ࢣࣥࢫ3ࢆ⏝࠸࡚⾜ࡗࡓࠋ
2.1.3.

1H MAS & 1H DQMAS NMR ࢫ࣌ࢡࢺࣝ

ᐃ

ᅛయ1H MAS NMR࠾ࡼࡧ1H DQMAS NMRࢫ࣌ࢡࢺࣝ ᐃࡣࠊ㟼☢ሙ18.8T(1H ඹ㬆࿘Ἴᩘ800 MHz
Bruker-AVANCE800ศගィࢆ⏝࠸࡚ᐇ᪋ࡋࡓࠋ ᐃ࡟ࡣ஧㔜ඹ㬆ᑐᛂ0.7mmĳࣉ࣮ࣟࣈࢆ⏝࠸ࡓࠋ
1H MAS NMRࢫ࣌ࢡࢺࣝ

ᐃࡣࠊᅇ㌿࿘Ἴᩘ100 kHzࡢୗ࡛ࠊࣂࢵࢡࢢࣛ࢘ࣥࢻࢩࢢࢼࣝࢆ༑ศ࡟

ୗࡆࡿࡓࡵDEPTHࢩ࣮ࢣࣥࢫ4ࢆ⏝࠸ࠊ90oࣃࣝࢫᖜ 1.2 ȝs, ⧞ࡾ㏉ࡋ᫬㛫 15 sࠊ✚⟬ᅇᩘ3200ᅇࡢ
᮲௳࡛ᐇ᪋ࡋࡓࠋ1H DQ (Double Quantum) MAS ࢫ࣌ࢡࢺࣝࡣࠊBABA16ࢩ࣮ࢣࣥࢫ5ࢆ⏝࠸࡚ࠊࣃࣝࢫᖜ 1.2 ȝs, ⧞ࡾ㏉ࡋ᫬㛫3sࠊྛt1࡛ࡢ✚⟬᫬㛫ࢆ192ᅇ࡜ࡋࡓࠋ
3.
29⤖ᯝ࠾ࡼࡧ⪃ᐹ
Si MAS NMR ࢫ࣌ࢡࢺࣝ࠾ࡼࡧ 29Si{1H}CPMAS ࢫ࣌ࢡࢺࣝࢆ Fig. 1 ࡟♧ࡍࠋᑒ⥸㣴⏕ 7 ᪥࡛ࡣࠊSiO4 ᅄ㠃యࡢከ㔜ᗘࡀ Q1 ࠾ࡼࡧ Q2 ࡢࢿࢵࢺ࣮࣡ࢡᵓ㐀࠿ࡽᵓᡂࡉࢀ࡚࠾ࡾࠊࡇࢀࡣࠊ࢝ࣝ
ࢩ࣒࢘ࢩࣜࢣ࢖ࢺỈ࿴≀㸦Calcium Silicate Hydrate: C-S-H㸧࠾ࡼࡧ୍㒊ᮍỈ࿴ࡢ Alite㸦3CaO࣭SiO2㸧,Belite(2CaO࣭SiO2)ࡢᏑᅾࢆ♧ࡋ࡚࠸ࡿࠋ29Si MAS ࢫ࣌ࢡࢺࣝ࠿ࡽศ࠿ࡿࡼ࠺࡟ࠊಁ㐍⎔ቃ୰ᛶ໬ᚋ࡟ࡣࠊ᫂ࡽ࠿࡟ࡇࢀࡽ Q1 ࠾ࡼࡧ Q2 ࡢẚ⋡ࡀపୗࡋࠊ᪂ࡓ࡟ Q4 ᵓ㐀ࡀ⏕ᡂࡋ࡚࠸ࡿࡇ࡜ࡀศ࠿
ࡿࠋࡇࢀࡣࠊỈ࿴≀ࡀศゎࡉࢀࡿ㝿࡟ࠊSi-O-Si ࡢࣈࣜࢵࢪᵓ㐀ࡀษ᩿ࡉࢀࠊ࢚ࢿࣝࢠ࣮ⓗ࡟Ᏻᐃ໬ࡍࡿࡼ࠺࡟ࠊᅄ㠃యࡀ⥙┠≧࡟ᡂ㛗ࡋࡓࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋࡇࡢ Q4 ┦ᙜ㡿ᇦࡣࢫ࣌ࢡࢺࣝࡢ༙
್ᖜࡀ኱ࡁࡃᵓ㐀ⓗ࡞ศᕸࢆ♧ࡋ࡚࠾ࡾࠊ⤖ᬗ┦࡛ࡣ࡞ࡃ㠀ᬗ㉁࡛࠶ࡿࡇ࡜ࡀᙉࡃ♧၀ࡉࢀࡿࠋ
ụ⏣ࡽ 5 ࡣࠊC-S-H ࡛ࡣ↓࠸ࡀࠊࡇࢀ࡜㢮ఝࡋࡓᵓ㐀ࢆ᭷ࡍࡿࢺࣂࣔࣛ࢖ࢺࡢⅣ㓟໬(୰ᛶ໬)㐣⛬ࢆ◊✲ࡋࠊࢺࣂࣔࣛ࢖ࢺࡢศゎ࡟ࡼࡿ㠀ᬗ㉁ࢩࣜ࢝ࢤࣝࡢ⏕ᡂ࡟ゝཬࡋ࡚࠾ࡾࠊ௒ᅇࡢほ⤖ᯝࡶࡇࢀ࡜ᩚྜⓗ࡛࠶ࡿࠋ29

Si{1H}CPMAS ࢫ࣌ࢡࢺࣝࡼࡾࠊ඲࡚ࡢヨᩱ࡟ࡘ࠸࡚ Q1 ┦ᙜ㡿ᇦࡢࢩࢢࢼࣝࡣⴭࡋࡃῶ⾶ࡋ࡚－ 193 －

࠾ࡾࠊࡇࢀࡣࠊ㹆ཎᏊࡀ㏆ഐ࡟Ꮡᅾࡋ࡞࠸ࠊ༶ࡕ
ࢡ࣮࡛ࣜࣥ࢝࠶ࡿࡇ࡜
ࢆ♧ࡋ࡚࠸ࡿࠋࡲࡓࠊಁ
㐍⎔ቃ࡜ᐊෆ⎔ቃࢆẚ࡭ࡿ࡜ࠊᐊෆ⎔ቃୗ࡟࠾࠸࡚ࠊከ㔜ᗘࡀపࡃࠊ
ඖࠎࡢࢭ࣓ࣥࢺỈ࿴≀ࡀṧᏑࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ Si ࡢ໬Ꮫᵓ㐀᝟ሗࡼࡾࠊಁ㐍⎔ቃ࡛ࡣ㧗⅔ࢭ
࣓ࣥࢺ୰ࡢỈ࿴≀ࡢศゎࡀಁ㐍ࡉࢀࠊᐊෆ⎔ቃ

Fig. 1. Summary of 29Si MAS and Si{1H}CPMAS NMR spectra of GGBS cement pastes
before and after carbonation. (a) :sealing cure. (b): atmospheric carbonation, (c): accelerated
carbonation.

࡛ࡢ୰ᛶ໬࡟ẚ࡭ࠊຎ໬ࡀ㐣๫࡟㐍⾜ࡍࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
ࡇࡢ௬ㄝࢆ᳨ドࡍࡿࡓࡵࠊ27Al MAS ࡜ 1H MAS ࡢゎᯒࢆᐇ᪋ࡋࡓࠋ
27Al MAS NMR ࢫ࣌ࢡࢺࣝࢆ Fig. 2 ࡟♧ࡍࠋࡇࢀࡽࡢࢫ࣌ࢡࢺࣝࡼࡾࠊᑒ⥸㣴⏕ 7 ᪥ᚋ࡟ࡣࠊ

໬Ꮫࢩࣇࢺ 0㹼10ppm ࡢ 6 㓄఩ Al 㡿ᇦ࡟ࠊMonosulphate㸦Ca4Al2O6SO4 ࣭12H2O㸧, Ettringite
㸦Ca6Al2(SO4)3(OH)12·26H2O㸧, ⾲㠃྾╔ Al㸦᥎ᐃ㸧ࡀほ ࡉࢀࡓࠋࡲࡓࠊ4 㓄఩ Al ࡶほ ࡉࢀ࡚࠾ࡾࠊࡇࢀࡣ C-S-H ࡢ SiO4 ᅄ㠃య࡟࠾࠸࡚ࠊSi ࢆ⨨᥮ࡋࡓࡶࡢ࡜⪃࠼ࡽࢀࡿࠋࡉࡽ࡟ࠊᏑᅾ㔞ࡣ㠀ᖖ࡟ᑡ࡞࠸ࡀࠊ5 㓄఩ Al ࡶほ ࡉࢀࡓࠋಁ㐍⎔ቃ୰ᛶ໬ᚋ࡟ࡣࠊ୰ᛶ໬๓࡟Ꮡᅾࡋࡓ Ettringite ࡀᾘኻࡋ Monosulphate ࡶ኱ᖜ࡟ῶᑡࡍࡿ
࡞࡝ࠊ6 㓄఩ Al ᵓ㐀ࢆ᭷ࡍࡿࢭ࣓ࣥࢺỈ࿴≀ࡀ࡯࡜ࢇ࡝ศゎࡋ࡚࠸ࡓࠋࡑࡢ୍᪉࡛ࠊ໬Ꮫࢩࣇࢺ
40~80ppm ௜㏆ࡢ 4 㓄఩ Al ࡣቑ኱ࡋ࡚࠸ࡓࠋࡇࢀࡣࠊࢭ࣓ࣥࢺỈ࿴≀୰࡟Ꮡᅾࡋ࡚࠸ࡓ 6 㓄఩ Al
ࡀࠊỈ࿴≀ࡢศゎ࡟క࠸ 4 㓄఩ Al ࡟ᵓ㐀ኚ໬ࡋࡓࡓࡵ࡜⪃࠼ࡽࢀࠊQ4 ᵓ㐀ࢆ᭷ࡍࡿ཯ᛂ⏕ᡂ≀ࡢ୍㒊ࢆᵓᡂࡋ࡚࠸ࡿྍ⬟ᛶࡀ࠶ࡿࠋࡲࡓࠊFig. 2 ࠿ࡽ᫂ࡽ࠿࡞ࡼ࠺
࡟ࠊࡇࡢ 4 㓄఩ Al ࡢẚ⋡ࡣࠊಁ㐍⎔ቃࡢ᪉ࡀᐊෆ⎔ቃࡼࡾ㧗࠿ࡗࡓࠋࡇࡢഴྥ࡜ᩚྜࡍࡿࡼ࠺࡟ࠊᐊෆ⎔ቃࡢヨᩱ࡛ࡣࠊEttringite ࡀ୍㒊ṧᏑ
ࡋࠊMonosulphate ࡢṧᏑẚ⋡ࡶ㧗࠸ࡇ࡜ࡶศ࠿ࡗࡓࠋ
௨ୖࡢࡼ࠺࡟ࠊ
Al ࡢ໬Ꮫᵓ㐀᝟ሗ࠿ࡽࡶࠊಁ㐍⎔ቃ࡜ᐊෆ⎔ቃ࡛ࡣᵓ㐀࡟ᕪ␗ࡀ࠶ࡾࠊಁ㐍୰ᛶ໬ࡣ㧗⅔
ࢭ࣓ࣥࢺࡢຎ໬ࢆࡼࡾ㐍⾜ࡉࡏࡿࡇ࡜ࡀᙉࡃ♧၀ࡉࢀࡓࠋ ࡉࡽ࡟ࠊྛヨᩱࡢ 1H MAS NMR

Fig. 2. Summary of 27Al NMR spectra of GGBS cement pastes before andafter carbonation. (a):sealing cure. (b):atmospheric carbonation, (c):accelerated carbonation.

ࢫ࣌ࢡࢺࣝ࠾ࡼࡧ 1H DQMAS ࢫ࣌ࢡࢺࣝࢆ Fig. 3 ࡟♧ࡍࠋ඲࡚ࡢヨᩱ࡟ඹ㏻ࡋ࡚ほ ࡉࢀࡿࡢࡣࠊ୺࡟໬Ꮫࢩࣇࢺ 4㹼8 ppm ௜㏆ࡢᗈᖜ࡞ࣆ࣮ࢡ (X)ࠊ2－ 194 －

ppm ௜㏆ࡢẚ㍑ⓗඛ㗦ⓗ࡞ࣆ࣮ࢡ(Y)ࠊࡉࡽ࡟ࡣ 1 ppm ௜㏆ࡢࣆ࣮ࢡ(Z)ࡢィ 3 ࡘࡢࣆ࣮ࢡ࡛࠶ࡿࠋ
ࡇࡢ࠺ࡕࠊࣆ࣮ࢡ X ࡟㛵ࡋ࡚ࡣࠊࢭ࣓ࣥࢺヨᩱ୰࡟⤖ྜỈ➼࡛Ꮡᅾࡋ࡚࠸ࡿỈศᏊ㸦H2O㸧࡜⪃࠼ࡽࢀࡿࠋ୍᪉ࠊࣆ࣮ࢡ Y ࠾ࡼࡧ Z ࡟㛵ࡋ࡚ࡣࠊC-S-H, Ettringite ࠾ࡼࡧ Monosulpahte ➼ࡢ OH ᇶࡸỈศᏊ࡟⏤᮶ࡍࡿࡶࡢ࡜⪃࠼ࡽࢀࡿࠋ
୰ᛶ໬ࡋࡓヨᩱ㸦(b)࠾ࡼࡧ(c)㸧࡛ࡣࠊY, Z ࡢࣆ࣮ࢡᙉᗘࡀపୗࡋࠊ┦ᑐⓗ࡟ X ࡢࣆ࣮ࢡᙉᗘࡀ
ቑຍࡋࡓࠋ (b)࡜(c)ࡢẚ㍑ࡼࡾࠊᐊෆ⎔ቃ(c)ࡢ᪉ࡀࠊࣆ࣮ࢡ Y ࠾ࡼࡧ Z ࡢᙉᗘࡀ㧗ࡃࠊಁ㐍⎔ቃ(b)࡟ẚ࡭࡚Ỉ࿴≀ࡀṧᏑࡋ࡚࠸ࡓࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋࡇࡢⅬࡣࠊࡇࢀࡲ࡛࡟♧ࡋࡓ Si ࠾ࡼࡧ Al
ࡢ໬Ꮫᵓ㐀ゎᯒ⤖ᯝ࡜ࡶ୍⮴ࡍࡿഴྥ࡛࠶ࡿࠋ ࡲࡓࠊ1H DQMAS NMR ࢫ࣌ࢡࢺࣝࡼࡾࠊほ ࡉࢀࡓ H ࢧ࢖ࢺࡣࠊ඲⯡ⓗ࡟௚ࡢࢧ࢖ࢺ࡜ࡢ┦㛵ࡀṤ࡝↓࠸࠿ࠊ㠀ᖖ࡟ᚤᙅ࡛࠶ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ୰ᛶ໬๓(a)࡜ᐊෆ⎔ቃ୰ᛶ໬ᚋ(c)࡛ࡣࠊ1H
MAS ࢫ࣌ࢡࢺࣝ(A)ࡢ Y ࡜ Z ࡟┦ᙜࡍࡿ㡿ᇦ࡟࠾࠸࡚ᚤᙅ࡞┦㛵ࡀᤊ࠼ࡽࢀ࡚࠸ࡓࡀࠊFig. 3 ࡟♧ࡍࡼ࠺࡟ಁ㐍୰ᛶ໬ᚋ࡟ࡣࡑࡢ┦㛵ࡣኻࢃࢀࠊH2O ࡸ OH ᇶࡢ┦஫స⏝ࡣࡼࡾ୍ᒙపୗࡋ࡚࠸
ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡇࡢࡼ࠺࡟ࠊH ࡢ໬Ꮫᵓ㐀᝟ሗ࠿ࡽࡶࠊಁ㐍⎔ቃ࡜ᐊෆ⎔ቃࡢ㐪࠸ࡀㄆࡵࡽࢀࠊಁ㐍୰ᛶ໬ࡣ኱Ẽ୰ᛶ໬ࡼࡾࡶ㧗⅔ࢭ࣓ࣥࢺ࡟ᑐࡋ኱ࡁ࡞ࢲ࣓࣮ࢪࢆ୚࠼ࡿྍ⬟ᛶࡀ♧ࡉ
ࢀࡓࠋ
B)

A)

Fig. 3. Summary of A) 1H MAS NMR spectra for (a) sealing cure, (b) atmospheric carbonation, (c) accelerated carbonation,
and B) 1H DQMAS NMR spectrum of carbonation under accelerated condition.

4.

⤖ゝ௒ᅇㄪᰝᑐ㇟䛸䛧䛯㧗⅔䝉䝯䞁䝖◳໬య䠄GGBS ⨨᥮⋡ 85%䠅䛻䛴䛔䛶䛿䚸ᅛయ NMR 䛻䜘䜛໬Ꮫᵓ㐀ゎᯒ䛾⤖ᯝ䚸ಁ㐍୰ᛶ໬䛸኱Ẽ୰ᛶ໬䛷䛿໬Ꮫᵓ㐀ኚ໬䛜᫂䜙䛛䛻␗䛺䜚䚸ಁ㐍⎔ቃ䛷䛿Ỉ࿴≀䛾ศゎ䛜ಁ㐍䛥䜜䚸ᐇ㝿䛾኱Ẽ⎔ቃ䜘䜚䜒㐣ᗘ䛻ຎ໬䛜㐍䜐䛣䛸䛜ุ᫂䛧䛯䚹䛧䛯䛜䛳䛶䚸㧗⅔䝉䝯䞁䝖䛻ᑐ䛩䜛ಁ㐍୰ᛶ໬ヨ㦂䛿䚸ᐇ⎔ቃ䛾୰ᛶ໬཯ᛂ䜢༢⣧䛻ຍ㏿໬䛧䛯䛰䛡䛺䛟䚸䜘䜚኱䛝䛺䝎䝯䞊䝆䜢䜒䛯䜙䛧䚸䛣䛾䛣䛸䛜䚸㧗⅔䝉䝯䞁䝖䛾⪏ஂᛶ䛾㐣ᑠホ౯䛻⧅䛜䛳䛶䛔䜛ྍ⬟ᛶ䛜䛒䜛䚹
References(1) ᯇᒸᘯ኱䚸ோᖹ㐩ஓ䚸ఀ⸨ṇ᠇䚸ᒣ⏣ஂ⨾㻌 㻔㻞㻜㻝㻡㻕㻌 䝁䞁䜽䝸䞊䝖ᕤᏛᖺḟㄽᩥ㞟㻌 37 1351-1356. (2) von GreveDierfeld, S., Lothenbach, B., Vollpracht, A. et al. Mater Struct 53, 136 (2020). (3) Z. Gan, and H.T. Kwak J. Magn. Reson. 168(2004) 346-351. (4) D. G. Cory, and W. M. Ritchey, J. Magn. Reson. 80 (1993) 128-132. (5) W. Sommer, J. Gottwald, D.E.
Demco, and H. W. J. Spiess, J. Magn. Reson. A 113 (1995) 131, (6) Y. Ikeda, Y. Yasuike and Y. Takashima (1991) J. Cer.
Soc.Jpn 99, 423-426.

－ 195 －P28Y

༟ ୖ NMRࢆ ⏝ ࠸ ࡓ ẕ ங ୰ ࡢ ࣛ ࢡ ࢺ ࣮ ࢫ ࡢ ᐃ 㔞‫ ▱ ⬌   ⛥ ె ⵓ ۑ‬ᙪ  ⏑ Ⳁ  Ᏽ Ꮚ ㇦  ኱ す ⿱ Ꮨ  㛗 ⏣ㄔ ྖ  ஂ ⡿ ⏣ ༤ அ  ⇃ ᮌ ᗣ ⿱  㸪 ᒣ ෆ ୍ ኵ  㸪 ┦ ἑ ᬛ ᗣ 
1 ໭ᾏ㐨኱Ꮫ࣭኱Ꮫ㝔⏕࿨⛉Ꮫ㝔
2 ୰ᒣၟ஦㸦ᰴ㸧
3 Ἀ⦖⛉Ꮫᢏ⾡኱Ꮫ㝔኱Ꮫ࣭ᶵჾศᯒࢭࢡࢩࣙࣥ

Quantification of lactose in human breast milk using benchtop NMR‫ ۑ‬Jiaxi JIANG 1 , Zhiyan HU 1 , Li GAN 1 , Zihao SONG 1 , Yuki Ohnishi 1 , Seiji Osada 2 ,Hiroyuki Kumeta 1 , Yasuhiro Kumaki 1 , Kazuo Yamauchi 3 , Tomoyasu Aizawa 1
1

Grad. Sch. Life Sci., Univ. Hokkaido

2Nakayama Co.,Ltd.

3

Instrumental Analysis Section, OISTHuman breast milk is the primary source of nutrition for neonates. Changes in thelactose concentration of breast milk have an essential impact on the growth of c hildren.
NMR is an attractive technology for quantifying lactose , and the recent emergence ofbenchtop NMR may address the high purchase and maintenance costs of high -field
NMR and can be used by point-of-care facilities. In this study, we investigated a
protocol for the determination of lactose in breast milk by bench -top NMR. The
reliability of the benchtop NMR was demonstrated by comparing the results of lactose
quantification in breast milk using benchtop NMR with 8 00 MHz NMR.
Overview
In comparison to high -field NMR using
expensive-superconducting

coils,

benchtop NMR uses permanent magnets,
which results in reduced investment andmaintenance costs and a smaller size.
However, on the other hand, as shown in
Fig. 1, the resolution and sensitivity ofbenchtop NMR is much lower than those
of

high

field

spectrometers. Fig. 1 Comparison of 1H spectra between
Furthermore, because benchtop NMR is 800 MHz NMR and 60 MHz NMR of thea newly developed device, there are nosame breast milk samples.

Benchtop NMR, Quantification, Human breast milk˕ ࡋ ࡻ ࠺ ࠿ ࡁ , ࡇ ࡋ ࡆ ࢇ 㸪࠿ ࢇ ࡾ 㸪ࡑ ࢇ ࡎ ࡣ ࠾ 㸪࠾ ࠾ ࡟ ࡋࡉࡔ ࡏ࠸ࡌ㸪ࡃࡵࡓ ࡦࢁࡺࡁ㸪ࡃࡲࡁ ࡸࡍࡦࢁ㸪ࡸࡲ࠺ࡕ࠸ࡊࢃ ࡜ࡶࡸࡍ

－ 196 －ࡺ ࠺ ࡁ 㸪࠾࠿ࡎ࠾㸪࠶well-established protocols. Therefore, in this study, a detailed examination of theconditions related to measurement and analysis was conducted to determine theconcentration of lactose in breast milk using bench -top NMR.
Methods and results
The selection of the power of the pre -saturated pulse can greatly affect the accuracyof the quantification results since the residual water signal will overlap with thelactose peaks. By comparing the spectra of the lactose standard sample obtained after
applying pre-saturation pulses of different powers , as shown in Fig. 2, it was foundthat the use of an appropriate pre-saturation pulse could effectively suppress the water
signal, with only a minor effect on the rest of the spectrum.
Next, the method of using TSP as an internal standard and the method ofquantification using calibration curve s built using standard lactose samples without
using an internal standard were examined.
7KH lactose standard curves were built using the spectra area of Ș -Lactose H1
peak and lactose bulk ring region of the lactose gradient samples . The obtained
standard curves were applied to quantify lactose in 18 human breast milk samples.
As shown in Fig.3, the dependability of using benchtop NMR for lactose
quantification was demonstrated by comparing the quantification results with thoseof the 800 MHz NMR equipment.

Fig. 2 impact of different pre -saturated pulse

Fig. 3 Errors in the quantification results ofpower settings on the spectra of 100 mM

lactose concentration in human breast milk

lactose standard samples.

using benchtop NMR.

－ 197 －

P29

Aggregation kinetics and Structural Insight of Į-synuclein Monomers
Cross-seeded with ȕ-amyloid Fibrils.
‫ ۑ‬Li Bing Kee1, Takayuki Kamihara1,2, Tatsuya Matsunaga2, Yoshiki Shigemitsu1,
Isamu Matsuda1, and Yoshitaka Ishii1,2
1School of Life Science and Technology, Tokyo Institute of Technology,

Yokohama, Japan.
2Advanced NMR Development & Application Team, BDR Center, RIKEN,

Yokohama, Japan.
Amyloid proteins, such as ȕ-amyloid (Aȕ) and Į-synuclein (ĮS), misfold into amyloid oligomers
and fibrils, are the common characteristics of various neurodegenerative diseases. Dementia with Lewy
bodies (DLB) and Parkinson’s disease (PD) are neurodegenerative disorders resulting from the accumulation
and aggregation of ĮS and the formation of Lewy bodies (LB) in brain. Alzheimer’s disease (AD) is aneurodegenerative disorder resulting from the abnormal assembly and misfolded Aȕ and the development ofamyloid plaques. Recent studies suggested that misfolded AE are frequently observed in DLB and PD patients,
implying a possible cross talk between ĮS and Aȕ aggregation. In this research, we monitor the aggregation
kinetics of ĮS monomers in the presence of Aȕ fibril “seed” using Thioflavin T (ThT) fluorescence assay,
while examining the morphology of ĮS fibrils via transmission electron microscopy (TEM). We will also
report the impact of the cross-seeding on structures of the resultant fibrils characterized by solid-state NMR(SSNMR).

The major pathological hallmark of PD is abnormal accumulation and aggregation of ĮS protein in
the form of Lewy bodies. Recent studies reported that misfolded ĮS exhibits structural differences in various
neurodegenerative diseases such as PD, DLB, and multiple system atrophy (MSA) [1,2,3]. AD ischaracterized pathologically by deposition of Aȕ plaques and formation of neurofibrillary tangles by tau
protein. Recent studies indicated co-existence of ĮS and Aȕ pathologies in many AD patients, suggesting
possible interaction between ĮS and Aȕ.[4] One hypothesis that explains the interaction is that ĮS and Aȕ
may exert cross-seeding effect from one to the other and can promote the aggregation [5,6]. Cross-seeding,which is also known as heterologous seeding, occurs when the polymerization of one amyloid protein iscatalyzed by aggregates of a different amyloid protein [7]. However, unlike self-seeding, in which aggregatesof the same amyloid protein are used as seed, the mechanisms of misfolding and aggregation of ĮS in various
cross-seeding conditions remain unclear. Also, there is a lack of studies on the structural details of amyloid
fibrils derived from such cross-seeding interactions using SSNMR.
In this study, the effects of cross-seeding on DS misfolding kinetics was monitored by incubating
DS monomer in the presence of AE40 fibril by ThT fluorescence, which selectively detects formation ofamyloid fibrils. The results were compared with those for unseeded and self-seeded DS samples.

alpha synuclein, cross-seeding, SSNMR‫ࡉ࠸ ࡔࡘࡲࠊࡁࡋࡼ ࡘࡳࡆࡋࠊࡸࡘࡓ ࡀ࡞ࡘࡲࠊࡁࡺ࠿ࡓ ࡽࡣࡳ࠿ࠊࣥࣅࣜ ࣮࢟ ۑ‬ࡴࠊ࠸ࡋ࠸ ࡼࡋࡓ࠿－ 198 －

The morphologies of the cross-seeded fibrils were inspected by TEM in comparison with those for selfseeded DS samples. We will also discuss the structural differences of self-seeded and cross-seeded fibrils
observed by SSNMR, which may provide some new insight into the correlation between AD and PD
pathogenesis.
References[1] Heise, H., Hoyer, W., Becker, S., Andronesi, O. C., Riedel, D., & Baldus, M. (2005) Molecular-levelsecondary structure, polymorphism, and dynamics of full-length Į-synuclein fibrils studied by solid-state
NMR. Proceedings of the National Academy of Sciences, 102 (44),16871-15876.
[2] Tuttle, M., Comellas, G., Nieuwkoop, A., Covell, D., Berthold, D., Kloepper, K., Courtney, J., Kim, J.,
Barclay, A., Kendall, A., Wan, W., Stubbs, G., Schwieters, C., Lee, V., George, J., & Rienstra, C. (2016)
Solid-state NMR structure of a pathogenic fibril of full-length human Į-synuclein. Nat Struct Mol Biol 23,
409–415.
[3] Schweighauser, M., Shi, Y., Tarutani, A., Kametani, F., Murzin, A., Ghetti, B., Matsubara, T., Tomita,
T., Ando, T., Hasegawa, K., Murayama, S., Yoshida, M., Hasegawa, M., Scheres, S., & Geodert, M. (2020)
Structures of Į-synuclein filaments from multiple system atrophy. Nature 585,464-469.
[4] Marsh, S. E., & Blurton-Jones, M. (2012). Examining the mechanisms that link ȕ-amyloid and Įsynuclein pathologies. Alzheimer's research & therapy, 4(2), 11.
[5] Paramita, C., Kailash, P. P., Bibin, G. A., Kriti, D., & Karunakar, K. (2019) Amyloid cross-seeding raises
new dimensions to understanding of amyloidogenesis mechanism. Ageing Research Reviews, 56, 1568-1637.
[6] Ono, K., Takahashi, R., Ikeda, T., & Yamada, M. (2012). Cross-seeding effects of amyloid ȕ-protein andĮ-synuclein. Journal of neurochemistry, 122(5), 883–890.
[7] Subedi, S., Sasidharan, S., Nag, N., Saudagar, P., & Tripathi, T. (2022) Amyloid Cross-Seeding:
Mechanism, Implication, and Inhibition. Molecules, 27(6):1776.

－ 199 －

P30

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7) 50-1%/B%0-12+ 5283" ,-668+ + ) 67) (7,%7>-162/87-21> 7,) '21*250%7-21%/*/) ;-&-/-7<-17,) /-1.) ( ',%-1 0-+ ,7 %//2: -7 72 '2-/ -172 %1 ?/-1) %5
32/<8&-48-7-1/-.) @ '21*250%7-21 :,-', 0-+ ,7 %//2:
-772-17) 5%'7:-7,     $-1%6-0-/%50%11) 5
" ,) 5) *25)  72 5) %66) 66 7,)  32/<8&-48-7-1

" ,)     $/-1) %5(-8&-48-7-1'2
'5<67%/ 6758'785)     5) * 

&-1(-1+ 63) '-*-'-7<2*     $-162/87-21%1(-1) ;3/%-160%1<%63) '762*7,) &-1(-1+ 352') 66<) 7

%1%720-'5) 62/87-21 0%11) 5:) 2&7%-1) (  -62723) 63) '7526'23<%33) %5672819) -/ %((-7-21%//%&) /) ( 385-*-) ( 3527) -1 6%03/) 6 %1( '21(8'7) ( () 7%-/6-162/87-21!3,) 5) $1 -21
62/87-21  7-75%7-21) ;3) 5-0) 17617-75%7-21) ;3) 5-0) 176 86-1+  /-1.) ((-8&-48-7-1:) %. 5) 6-(8%/&-1(-1+ 2*72     $(20%-1:%62&6) 59) (25) ;%03/) 5) 6-(8) 6      %1(2*7,)  $'25) 6,2:) ('/) %5/<() 7) '7%&/) ',) 0-'%/6,-*7',%1+ ) 683215%-6-1+ 7,) (-8&-48-7-172 $02/%55%7-2
2:) 9) 529) 5%//7,) &-1(-1+ %**-1-7<:%6() ) 0) (72&) :) %.%6%//2&6) 59) (',) 0-'%/6,-*7',%1+ ) 6:) 5) 
-17,) *%67) ;',%1+ ) 5) + -0) 217,)  7-0) 6'%/) %1(/) %67648%5) 6*-77-1+ 2*7,) ',) 0-'%/6,-*7',%1+ ) 6%6%*81'7-212*7,) '21') 175%7-216<-) /() (%  2*%3352;-0%7) /< F :,) 5) %663) '-*-'8&-48-7-1&-1(-1+ 2*7) 12''856:-7,  9%/8) 6-17,) 5%1+ ) 2* > F " ,867,) 6) 5) 68/76 %+ 5) ) ( :-7,7,) 35) 9-286/<() 6'5-&) (29) 5%//:) %.02128&-48-7-1&-1(-1+ 7) 1() 1'<2* 7,)  $(20%-1 *%0-/<167%5.'2175%67 

7-75%7-21 ) ;3) 5-0) 176 86-1+ /-1) %5 (-8&-48-7-1-1(-'%7) (%,-+ ,/<63) '-*-'

,-+ ,%**-1-7<&-1(-1+ 352') 6617,-6'%6)  

%0-() 5) 621%1') 6) -7,) 56,2:) (6-+ 1-*-'%17&52%() 1-1+ 29) 5

7,) '2856) 2*7,) 7-75%7-21-) -17) 50) (-%7) ) ;',%1+ ) 5) + -0) 217,)  7-0) 6'%/) 2567%57) (72(-6%33) %5

-17,) *5) ) 67%7) 727,) 15) %33) %5-17,) &281(67%7) -)  6/2:) ;',%1+ ) 5) + -0) 217,)  
-167%1') 7,) 6-+ 1%/'255) 6321(-1+ 727-0) 6'%/) 25

+ 5%(8%//<(-6%33) %5) (-17,) *5) ) 67%7) %1(7,) 15) %33) %5) (-17,) &281(67%7) :,-/)   %1(  6,2:) (+ 5%(8%/',) 0-'%/6,-*7',%1+ ) 6%/&) -7:-7,0%5.) (/-1) &52%() 1-1+ 29) 57,) '2856) 2*7,) 7-75%7-21" ,) 6) 7:25) 6-(8) 60%3727,) (-67%/8&-48-7-1&-1(-1+ 6-7) -17,) 5) 3257) ('2'5<67%/6758'785) :,-',) ;3/%-167,) -5/%5+ ) ',) 0-'%/6,-*73) 5785&%7-21%1(/-1) &52%() 1-1+ 8321-17) 5%'7-21
:-7, /-1) %5 (-8&-48-7-1 !-0-/%5/< "   %1(  5) 6-(8) 6 21 7,)  352;-0%/ # &&-1(-1+  6-7)  ) ;,-&-7) (75) 0) 1(286 /-1)  &52%() 1-1+  %7 -17) 50) (-%7)  02/%5 5%7-26  9) 5%// :)  '21'/8()  *520 7,) 6)  7-75%7-21) ;3) 5-0) 1767,%77,) '5<67%/6758'785) ) ;3/%-160%1<<) 7127%//%63) '762*62/87-2167%7) 8&-48-7-1&-1(-1+ " 2+ %-1*857,) 5-16-+ ,7-1723266-&/) 0) ',%1-67-'() 7%-/6-172/-1) %58&-48-7-1&-1(-1+ 63) '-*-'-7<:) %/62() 7) 50-1) (7,) <) 70-66-1+ 62/87-216758'785) 2*7,) *5) )  $(20%-12*    '203%5) (-76
6758'785%/5-+ -(-7<-1-76*5) ) %1(/-1) %58&-48-7-1&281(67%7) 6%1('21(8'7) (-627,) 50%/7-75%7-21'%/25-0) 75<%6:) //%66-7) (-5) '7) (087%+ ) 1) 6-6) ;3) 5-0) 176) *) 5) 1') 6
 *!""    )*&%%**" %$%+*&+!&$"%&$&,*)%&,%+&#"%)","(,"+"%          +&  '"")& %"+"&%&#"%),"(,"+"%!"%*.+!'# /"%"% )&$"%&+!*,,%"+&+!#"%),"(,"+"%!"%**$#.&$'#-      － 201 －

P31

ᅛయNMR࡜MDࢩ࣑࣮ࣗࣞࢩࣙࣥ࡟ࡼࡿࣄࢺ࢝ࣝࢩࢺࢽࣥࡢኚ␗
࡜ࢡࣝࢡ࣑ࣥῧຍ࡟ࡼࡿ⥺⥔ᙧᡂ㜼ᐖᶵᵓࡢゎ᫂‫ۑ‬ෆ⸨ ᬗ㸪ఀ⸨̿Ώ㑓 ࡦ࠿ࡾ2 ㇏⏣ಟᖹ1, Javkhlantugs Namsrai1,2, ᕝᮧ
ฟ1, ୖ⏣୍⩏11ᶓ὾ᅜ❧኱Ꮫ࣭኱Ꮫ㝔ᕤᏛ◊✲㝔
2ᅜ❧ࣔࣥࢦࣝ኱Ꮫ࣭ᕤᏛᛂ⏝⛉Ꮫ⛉

Fibril inhibition mechanism of human calcitonin by mutation and addition of curcumin
as revealed by solid state NMR and MD simulation‫ۑ‬Akira Naito1, Hikari Itoh-Watanabe1, Shuhei Toyoda1, Namsrai Javkhlantugs1,2, Izuru Kawamura1,
Kazuyoshi Ueda1
1 Graduate School of Engineering, Yokohama National University
2 School of Engineering and Applied Science , National University of Mongoria

Human Calcitonin (hCT) is known as an amyloid forming peptide. We have investigated that hCT fibrils
form cross E-sheet structure and Y12, F16, F19 and F22 play important role for the interaction between Estrands in fibrils using solid-state NMR spectroscopy and MD simulations. It is also investigated that hCTfibrils are formed by taking two step autocatalytic reaction mechanism with nucleation (k1) and fibril
elongation (k2) steps. In this study, firstly fibril formation kinetics were investigated with TL-hCT (Y12L,
F16L, F19L) mutants. Experimental results indicate that the rate of fibril elongation step was significantly
slowed, indicating that the fibril elongation process is inhibited by the mutation. Second, fibril forming
kinetics of hCT by addition of curcumin was investigated and the results indicate that the fibril nucleation
rate was significantly increased. This result indicates that curcumin actually inhibit the fibril nucleation step.
[ᗎᗎ]ࣄࢺ࢝ࣝࢩࢺࢽࣥ(hCT)ࡣ㸱㸰࢔࣑ࣀ㓟ṧᇶ࠿ࡽ࡞ࡿ࡮ࣉࢳࢻ࡛࣍ࣝࣔࣥࠊ⏥≧⭢࡛ศἪࡉࢀ࡚㦵ࡢ௦ㅰㄪ⠇࡟㔜せ࡞ᙺ๭ࢆᯝࡓࡋ࡚࠸ࡿࠋ୍᪉ࠊ㹦CTࡣ࢔࣑ࣟ࢖ࢻᵝ⥺⥔ࢆᙧᡂࡍࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠾ࡾࠊࡇࡢ࢔࣑ࣟ࢖ࢻ⥺⥔ࡣ⏥≧⭢㧊ᵝ࢞ࣥࢆㄏⓎࡍࡿࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠸ࡿࠋᡃࠎࡣࡇࢀ
ࡲ࡛ࠊ㹦CTࡢ⥺⥔ᵓ㐀ࡸ⥺⥔ᙧᡂᶵᵓࢆゎ᫂ࡍࡿ◊✲ࢆ⾜ࡗ࡚ࡁࡓ(1-4)ࠋ㹦CT࡟ࡼࡾᙧᡂࡉࢀࡓ
࢔࣑ࣟ࢖ࢻ⥺⥔࡟ࡘ࠸࡚ᅛయNMRศගἲࢆ⏝࠸࡚⥺⥔ᵓ㐀ࢆゎᯒࡋࡓ⤖ᯝࠊFig. 1 ࡟♧ࡍࡼ࠺࡟୰ᛶ⁐ᾮ୰࡛ᙧᡂࡋࡓ⥺⥔ࡣ㏫ᖹ⾜E-ࢩ࣮ࢺᵓ㐀ࢆᙧᡂࡋ࡚࠾ࡾࠊY12, F16, F19, F22ࡢⰾ㤶᪘࢔࣑ࣀ㓟ṧᇶࡀE-ࢫࢺࣛࣥࢻ㛫࡛┦஫స⏝ࢆᙧᡂࡋࠊ⥺⥔ࡢᏳᐃ໬࡟ᐤ୚ࡋ࡚࠸ࡿࡇ࡜ࡀ᫂ࡽ࠿࡟
࡞ࡗࡓࠋࡉࡽ࡟ᮏ◊✲࡛ࡣhCT࢔࣑ࣟ࢖ࢻ⥺⥔ᙧᡂ཯ᛂᶵᵓࡢゎ᫂ࢆ⾜ࡗ࡚ࡁࡓࠋ㹦CTࡢ࢔࣑ࣟ࢖ࢻ⥺⥔ᙧᡂࡣࣔࣀ࣐࣮ࡢ㹦CTࡀจ㞟ࡋ࡚⥺⥔୰㛫యࢆᙧᡂࡍࡿ཯ᛂ㸦㏿ᗘᐃᩘ㸸k1㸧ࢆ⤒࡚ࠊḟ࡟୰㛫యࡢ⾲㠃ࡀゐ፹࡜࡞ࡾ୰㛫య⾲㠃࡟㹦CTࣔࣀ࣐࣮ࡀ⥺⥔࡟ఙ㛗ࡋ࡚࠸ࡃ཯ᛂ㸦㏿ᗘᐃᩘ㸸k2㸧࡟ࡼࡾ⥺⥔ࡀᡂ㛗ࡋ࡚࠸ࡃ2ẁ㝵⮬ᕫゐ፹཯ᛂᶵᵓ࡟ࡼࡾゎᯒ࡛ࡁࡿࡇ࡜ࢆ♧ࡋ࡚ࡁࡓ(1)ࠋ
ᅛయNMRࠊࣄࢺ࢝ࣝࢩࢺࢽࣥ㸪⥺⥔ᙧᡂ㜼ᐖᶵᵓ‫ࡽࡁ࠶࠺࡜࠸࡞ۑ‬㸪࠸࡜࠺࣮ࢃࡓ࡞࡭ࡦ࠿ࡾࠊ࡜ࡼࡔࡋࡹ࠺࡬࠸ࠊ࡞ࡴࡎࡽ࠸ࡌࡷࡪ࠿ࡽࢇࡓࡄ
ࡍࠊ࠿ࢃࡴࡽ࠸ࡎࡿࠊ࠺࠼ࡔ࠿ࡎࡼࡋ

－ 202 －

ᮏ◊✲࡛ࡣࡇࢀࡲ࡛ࡢ◊✲ᡂᯝࢆࡶ࡜࡟⥺⥔ᙧᡂࢆ㜼ᐖࡍࡿᶵᵓ࡟ࡘ࠸࡚ヲࡋ࠸᳨ウࢆ⾜ࡗࡓࠋ㸯␒┠ࡣ㹦CTࡢ⥺⥔ᵓ㐀ࡢᏳᐃ໬࡟ⰾ㤶᪘࢔࣑ࣀ㓟ṧᇶࡀᐤ୚ࡋ࡚࠸ࡿࡇ࡜࠿ࡽࠊࡇࡢⰾ㤶᪘࢔࣑ࣀ
㓟(Y, F)ࢆL࡟ኚ␗ࡋࡓTL-㹦CT(Y12L, F16L, F19L)
࡟ࡘ࠸࡚⥺⥔ᙧᡂ཯ᛂᶵᵓࢆゎᯒࡋࡓࠋ2␒┠࡟ࢡࣝࢡ࣑ࣥࡀⰾ㤶᪘࢔࣑ࣀ㓟࡜┦஫స⏝ࡍࡿࡇ࡜࠿
ࡽࠊࢡࣝࢡ࣑ࣥࢆຍ࠼ࡓ㹦CT⁐ᾮ୰࡛㉳ࡇࡿ㹦CT
ࡢ⥺⥔ᙧᡂ཯ᛂᶵᵓ࡟ࡘ࠸࡚ゎᯒࡋࡓࠋࡇࢀࡽࡢ
⤖ᯝ࠿ࡽᚓࡽࢀࡓhCT⥺⥔ᙧᡂ㜼ᐖᶵᵓ࡟ࡘ࠸࡚
ሗ࿌ࡍࡿࠋ
[㹦
㹦CT࢔
࢔࣑ࣟ࢖ࢻ⥺⥔ࡢᵓ㐀ゎᯒ(1),(2),(3)]hCTࡣ୰ᛶ⁐ᾮ୰࡛▷᫬㛫ࡢ࠺ࡕ࡟⥺⥔ࢆᙧᡂࡋỿẊࢆ⏕ᡂࡋࡓࠋ㑅ᢥⓗ࡟ྠ఩యᶆ㆑ࡋࡓ
[13CO]Phe22,[13C3]Ala31-hCT, ࠾ ࡼ ࡧ [13CO]Gly10,[13C3]Ala26-hCT ࡢ ⥺ ⥔ ࡟ ࡘ ࠸ ࡚ CP-MAS

ᅛయ

NMRಙྕࢆほ ࡋࡓ࡜ࡇࢁࠊG10-F22ࡢ㡿ᇦ࡛E-ࢩ

Fig. 1: Structures of hCT fibril. (a) Cross Esheet structure was formed as revealed bysolid-state NMR. (b) Interaction were formed
between E-strands (F16-F19; SSinteraction,
D15-K18; electrostatic interaction, Y12-F22;
SSinteraction) at pH 7.5. (3)࣮ ࢺ ࢆᙧ ᡂࡋ ࡚࠸ ࡿࡇ࡜ ࡀ ุ᫂ ࡋࡓ ((1), Figure1a)ࠋࡉࡽ࡟[13CO]Phe16, [15N]Phe19-hCTࡢ⥺⥔࡟ࡘ
࠸࡚ 13C-15N ཎᏊ㛫㊥㞳ࢆREDORἲ࡟ࡼࡾᐃࡋࡓ⤖ᯝࠊPhe16, Phe19ࡀ㏆᥋ࡍࡿ㏫ᖹ⾜E-ࢩ࣮ࢺᵓ㐀ࢆᙧᡂࡍࡿࡇ࡜ࡀุ᫂ࡋࡓ(2)ࠋࡇࡢᵓ㐀࡟ࡘ࠸
࡚MDࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⏝࠸࡚ᵓ㐀ィ⟬ࢆ⾜࠸ࠊࡑࡢ┦஫స⏝ࢆゎᯒࡋࡓ⤖ᯝࠊE-ࢫࢺࣛࣥࢻ㛫
࡛ࠊF16-F19 (SS ┦஫స⏝), D15-K18㸦㟼㟁┦஫స⏝㸧, Y12-F22 (p-p ┦஫స⏝) ࢆᣢࡘࡇ࡜ࡀุ
᫂ࡋࡓ((3), Figure 1b)ࠋ[ 㹦 CT ࢔ ࣑ ࣟ ࢖ ࢻ ⥺ ⥔ ᙧ ᡂ ཯ ᛂ ᶵ ᵓ ࡢ ゎ ᯒ(1),(4)]
㹦CTࡢ⥺⥔ᙧᡂ཯ᛂࡢ᫬㛫ኚ໬ࢆCP-MASࡢಙྕᙉᗘኚ໬࡛ほ ࡋࡓ⤖ᯝࠊFigure 2a࡟♧ࡍಙྕᙉᗘኚ໬ࡀほ ࡉࢀࡓࠋࡇࡇ࡛ࠊCP-MASಙྕࡢ᫬㛫ኚ໬ࡣhCTࡢ⥺⥔ᙧᡂ㐣⛬ࢆ♧ࡋ࡚࠸ࡿࠋࡇ
ࡢಙྕᙉᗘࡢ᫬㛫ኚ໬ࡣ୍ᐃࡢ㐜ᘏ᫬㛫ࡢᚋ࡟ᙉᗘࡢቑຍࡀほ ࡉࢀࡓࠋࡇࡢࡼ࠺࡞⥺⥔ᙧᡂ཯ᛂࡣ⥺⥔୰㛫య㸦᰾㸧ࢆ⤒࡚ࠊ⥺⥔ఙ㛗཯ᛂࡀ㉳ࡇࡗ࡚࠸ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿ(4)ࠋࡇࡢ཯ᛂࢆ2ẁ㝵⮬ᕫゐ፹཯ᛂᶵᵓࢆ⏝࠸࡚ゎᯒࡋࡓࠋࣔࣀ࣐࣮
≧ែࡢ㹦CTࡢ⃰ᗘࢆA,⥺⥔≧ែࡢ㹦CTࡢ⃰ᗘࢆ

Fig. 2: hCT fibrillation mechanism. (a): Timecourse of CP-MAS (fibril) and DD-MAS(monomer) NMR signal intensities. (b):Fibrillation process of hCT in neutral solution.
The k1 is rate constant of nucleation step and k2
indicates fibril elongation step (1), (4).

B࡜ࡋ࡚཯ᛂ㏿ᗘࢆゎᯒࡋࡓ(1)ࠋ㸯ẁ㝵┠ࡢ୰㛫య㸦᰾㸧ࡢᙧᡂ཯ᛂࡣ

－ 203 －

k1
noA l Ano ĺ Bno[1] (Nucleation)2ẁ㝵┠ࡢ⥺⥔ఙ㛗཯ᛂࡣ
k2
A+Bn ĺ Bn+1

[2]

(Fibril elongation)ࡇࢀࡽ㸰ࡘࡢ཯ᛂࢆ⤌ࡳྜࢃࡏࡓ㏿ᗘᘧࡣ(dt/dt) = k1(1-f) + k2af(1-f)[3]࡜࡞ࡾࠊࡑࡢ୍⯡ゎࡣEq. [4]࡜࡞ࡿࠋ
ఘሼୣ୶୮ሾሺଵାఘሻ௞௧ሿିଵሽ ൌ ሼଵାఘ ୣ୶୮ሾሺଵାఘሻ௞௧ሿሽ      [4]ࡇࡇ࡛ࠊf: Fraction of B, a: Initial concentration of B,
s=k1/k, k=ak2 ࡛࠶ࡿࠋEq. [4] ࢆ⏝࠸࡚ࠊ᰾ᙧᡂ㏿ᗘᐃᩘ(k1), ⥺⥔ఙ㛗㏿ᗘᐃᩘ(k2)ࢆồࡵࡓࠋ㹦CT(Y12L, F16L, F19L)ኚ
ኚ␗య࡟࠾ࡅࡿ⥺[TL-㹦⥔ᙧᡂ㜼ᐖᶵᵓࡢゎ᫂ (3)]ᵓ㐀ゎᯒࡢ⠇࡛㏙࡭ࡓࡼ࠺࡟ⰾ㤶᪘࢔࣑ࣀ㓟ṧᇶTyr12, Phe16, Phe19ࡣ⥺⥔ࡢᏳᐃ໬࡟ᐤ୚ࡋ

Fig. 3: Fibrillation mechanism of TL-hCT mutant.
(a)Time courses of DD-MAS (monomer) and CPMAS (fibril) signals of TL-hCT mutant. (b) Timecourse of signal intensities (fraction of fibril) of
hCT and TL-hCT (3).

࡚࠸ࡿࡇ࡜ࡀண᝿ࡉࢀࡓࠋࡑࡇ࡛ࠊY, FࢆL࡟ኚ␗ࡋࡓTL-㹦CT㸦Y12L, F16L, F19L㸧ኚ␗యࢆ⏝࠸࡚⥺⥔ᙧᡂ㏿ᗘ㐣⛬ࢆゎᯒࡋࡓࠋFigure 3, Table
1࡟♧ࡍࡼ࠺࡟ࠊTL-㹦CTࡢ᰾ᙧᡂ㏿ᗘ(k1)ࡣ㹦CT
࡜ẚ㍑ࡋ࡚኱ࡁ࡞ኚ໬ࡣ࡞࠸ࡀࠊ⥺⥔ఙ㛗㏿ᗘᐃ
ᩘ(k2)࡟ࡘ࠸࡚TL-㹦CTࡣ㹦CT࡟ẚ࡭࡚኱ࡁࡃῶ
ᑡࡋ࡚࠸ࡿࡇ࡜ࡀほ ࡉࢀࡓࠋⰾ㤶᪘࢔࣑ࣀ㓟ṧ
ᇶࡣ㏫ᖹ⾜E-ࢩ࣮ࢺᵓ㐀ࡢᏳᐃ໬࡟ᐤ୚ࡋ࡚࠸ࡿ
ࡇ࡜࠿ࡽࠊⰾ㤶᪘࢔࣑ࣀ㓟ࡢY. F ࠿ࡽL࡬ࡢኚ␗ࡣ⥺⥔ࡢᏳᐃᛶࢆୗࡆࡿࡓࡵࠊ⥺⥔ఙ㛗㐣⛬ࡀ㜼ᐖࡉࢀࡓࡶࡢ࡜⪃࠼ࡽࢀࡿࠋ
[ࢡࢡࣝࢡ࣑ࣥ࡟ࡼࡿ㹦CT⥺⥺⥔ᙧᡂ㜼ᐖᶵᵓࡢ
ゎ᫂]ࢡࣝࢡ࣑ࣥࡣⰾ㤶⎔ࢆศᏊ୰࡟ྵࡴࡓࡵD-࣊ࣜࢵࢡࢫᵓ㐀ࢆࡶࡘhCTࣔࣀ࣐࣮࡟ࢡࣝࢡ࣑ࣥࡀ࡝ࡢ
ࡼ࠺࡞┦஫స⏝ࢆᣢࡘࡢ࠿ࢆMDࢩ࣑࣮ࣗࣞࢩࣙ
ࣥ࡟ࡼࡾ᳨ドࡋࡓࠋࡑࡢ⤖ᯝࠊFigure 4࡟♧ࡍࡼ࠺
࡟㹦CT࣊ࣜࢵࢡࢫᵓ㐀࡟ᏑᅾࡍࡿF16, F19, H20ࡣ

－ 204 －

Fig.4: Interaction of curcumin with hCT
monomer revealed by MD simulation.
Interaction between hCT monomer andcurcumin are forming T-shapedSS (F19Cur). CH-O (F16-Cur) and parallel SS H20Cur interactions.

ࢡࣝࢡ࣑ࣥ࡜┦஫స⏝ࢆࡋ࡚࠸ࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋࡑࡇ࡛TL-㹦CT࡟ࡘ࠸࡚ࢡࣝࢡ࣑ࣥᏑᅾୗ࡛
ࡢ⥺⥔ᙧᡂ㏿ᗘゎᯒࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊTable 2࡟♧ࡍࡼ࠺࡟ࠊࢡࣝࢡ࣑ࣥࡢᏑᅾୗ࡛ࡣ㹦CTࡢ
᰾ᙧᡂ㏿ᗘᐃᩘ(k1)ࡀࢡࣝࢡ࣑ࣥࡀ↓ῧຍࡢ≧ែ࡟ẚ࡭࡚᱁ẁ࡟㐜ࡃ࡞ࡿࡇ࡜ࡀุ᫂ࡋࡓࠋ୍᪉ࠊ
⥺⥔ఙ㛗㏿ᗘᐃᩘ(k2)࡟ࡣ኱ࡁ࡞ኚ໬ࡀぢࡽࢀ࡞࠿ࡗࡓࠋࡇࡢ⤖ᯝࡣࢡࣝࢡ࣑ࣥࡀ㹦CTࣔࣀ࣐࣮࡜┦஫స⏝ࢆᣢࡘࡓࡵࠊ㹦CTྠኈ࡛จ㞟ࡋ࡚᰾ࢆᙧᡂࡍࡿ㏿ᗘࡀ㐜ࡃ࡞ࡗࡓࡶࡢ࡜⪃࠼ࡽࢀࡿࠋ
ࡍ࡞ࢃࡕࢡࣝࢡ࣑ࣥࡣhCTࡢ᰾ᙧᡂ㐣⛬ࢆ㜼ᐖࡍࡿࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗࡓࠋ
Table 1: Rate constants of fibril formation kinetics for hCT and TL-hCT (3).
k1 (s-1): Nucleation

k2 (s-1M-1): Elongation

WT hCT

2.79 x 10-6

2.29

TL-hCT

3.40 x 10-6

2.98 x 10-3

Table 2: Rate constants of fibril formation kinetics for hCT in the presence of curcumin.
k1 (s-1): Nucleation

k2 (s-1M-1): Elongation

hCT

3.84 x 10-6

0.318

hCT + DMSO (30%)

1.25 x 10-8

0.442

hCT + DMSO (30%) + curcumin (0.210 mM)

3.13 x 10-10

0.294

ࡲ࡜ࡵ]
[ࡲ
ᮏ◊✲࡛ࡣ㹦CT࢔࣑ࣟ࢖ࢻ⥺⥔ᙧᡂࡢ㜼ᐖᶵᵓ࡟ࡘ࠸࡚2ࡘࡢሙྜࢆ᳨ウࡋࡓࠋ➨1ࡢሙྜࠊ⥺⥔ࡢᏳᐃ໬࡟ᐤ୚ࡍࡿY,FࢆL࡟ኚ␗ࡋࡓTL-hCT (Y12L, F16L, F19L)ኚ␗య࡟ࡘ࠸࡚㜼ᐖᶵᵓࢆ᳨ウࡋࡓ࡜ࡇࢁࠊ⥺⥔ఙ㛗㐣⛬ࢆ㜼ᐖࡍࡿࡇ࡜ࡀุ᫂ࡋࡓࠋ➨2ࡢሙྜࠊከࡃࡢ࣌ࣉࢳࢻࡸࢱࣥࣃࢡ㉁࡜┦஫స⏝ࢆᣢࡘࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࢡࣝࢡ࣑ࣥࢆῧຍࡋࡓ≧ែ࡛ࡢ㹦CT⥺⥔ᙧᡂ㜼ᐖᶵᵓࢆ᳨ウࡋࡓࠋࡑࡢ⤖ᯝࠊࢡࣝࢡ࣑ࣥࡣ㹦CTࣔࣀ࣐࣮࡜┦஫స⏝ࢆ♧ࡋࠊ㹦CTྠኈࡢจ㞟ࢆ㜼ᐖࡍࡿࠊࡍ࡞ࢃࡕ㹦CTࡢ᰾ᙧᡂ㐣⛬ࢆ㜼ᐖࡍࡿࡇ࡜ࡀุ᫂ࡋࡓࠋ
References(1) M. Kamihira, A. Naito, S. Tuzi, A. Y. Nosaka, H. Saito. (2000) Conformational transition and fibrillation
mechanism of human calcitonin as studied by high-resolution solid-state 13C NMR. Protein Science 9, 867877.
(2) A. Naito, M. Kamihira, R. Inoue, H. Saito. (2004) Structural diversity of amyloid fibril for,ed in humancalcitonion as revealed ny site-directed 13C solid-state NMR spectroscopy. Magn. Roson. Chem. 42, 247-257.
(3) H. Itoh-Watanabe, M. Kamihira-Ishijima, N. Javkhlantugs, R. Inoue, Y. Itoh, H. Endo, S. Tuzi, H. Saito,
K. Ueda, A. Naito. (2013) Role of aromatic residues in amyloid fibril formation of human calcitonin by solidstate 13C NMR and molecular dynamics simulation. Phys. Chem. Chem. Phys. 15, 8890-8901.
(4) H. Itoh-Watanabe, M. Kamihira-Ishijima, I. Kawamura, M. Kondoh, M. Nakagoshi, M. Sato, A. Naito.
(2013) Characterization of the spherical intermediates and fibril formation of hCT in HEPES solution usingsoid-state 13C-NMR and transmission electron microscopy. Phys. Chem. Chem. Phys. 15, 16956-16964.

－ 205 －

P32Y

㓟໬ࢳࢱࣥࢼࣀࢩ࣮ࢺ࡜㠀⏺㠃άᛶ๣ࢫࣝࣇ࢛࣋ࢱ࢖ࣥࢆ⏝࠸ࡓ
⺮ⓑ㉁ࡢRDC ᐃᡭἲ㛤Ⓨ‫ۑ‬ᯈᆏభ┿ࠊᑠ⠢⵬ࠊྂᯈᜤᏊࠊᮡᮌಇᙪࠊⱝᯇ㤾ࠊෆ⏣⣖அࠊ▼⏣ᗣ༤ࠊ┦⏣༟୕ࠊ⸨ཎᩄ㐨ࠊඣᔱ㛗ḟ㑻
1 ᶓ὾ᅜ❧኱Ꮫ኱Ꮫ㝔 ⌮ᕤᏛᗓ2 ኱㜰኱Ꮫ ⺮ⓑ㉁◊✲ᡤ
3 ⩌㤿኱Ꮫ኱Ꮫ㝔 ⌮ᕤᏛᗓ
4 ⌮໬Ꮫ◊✲ᡤ ๰Ⓨ≀ᛶ⛉Ꮫ◊✲ࢭࣥࢱ࣮
5 ᮾி኱Ꮫ኱Ꮫ㝔 ᕤᏛ⣔◊✲⛉Development of RDC measurement method for protein using titanium oxide nanosheets
and non-detergent sulfobetaines‫ۑ‬Yuma Itasaka1, Aoi Kokago1, Kyoko Furuita2, Toshihiko Sugiki2, Kaori Wakamatsu3, Noriyuki Uchida4,
Yasuhiro Ishida4, Takuzo Aida5, Toshimichi Fujiwara2, Chojiro Kojima1,2
1 Graduate School of Engineering Science, Yokohama National University
2 Institute for Protein Research, Osaka University
3 Graduate School of Science, Gunma University
4 Center for Emergent Matter Science, RIKEN
5 Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo
Residual dipolar coupling (RDC) provides long-range distance information and orientations of internuclear
vectors with respect to the magnetic field. RDC is valuable for structure determination, validation, anddynamics analysis of proteins. The measurement of RDC values requires the weak alignment of themacromolecule in the magnetic field. Various alignment media have been utilized to align protein molecules.
To determine the orientation of bond vectors accurately from RDC, five independent alignments are required.
In this study, we utilized new perpendicular alignment media, titanium oxide nanosheets (TiNSs), for protein
RDC measurement with the protein stabilizer, non-detergent sulfobetaine (NDSB).
࠙ᗎㄽࠚṧవ཮ᴟᏊ┦஫స⏝(RDC)ࡣࠊࣟࣥࢢࣞࣥࢪࡢ㊥㞳᝟ሗࡸ᰾㛫࣋ࢡࢺࣝࡢゅᗘ࡟㛵ࡍࡿ᝟ሗࢆ
୚࠼ࠊ⺮ⓑ㉁ࡢᵓ㐀ゎᯒࡸ᳨ドࠊࢲ࢖ࢼ࣑ࢡࢫࡢゎᯒ࡟฼⏝ࡉࢀ࡚࠸ࡿࠋ⁐ᾮ≧ែ࡟࡚RDCࢆ
ᐃࡍࡿࡓࡵ࡟ࡣࠊ⺮ⓑ㉁ࢆ☢ሙ୰࡛㓄ྥࡉࡏࡿᚲせࡀ࠶ࡿ [1]ࠋ⺮ⓑ㉁ࡢ☢ሙ㓄ྥ࡟ࡣ☢ሙ㓄ྥ๣ࡀ฼⏝ࡉࢀ࡚࠸ࡿࠋRDC࠿ࡽ᰾㛫࣋ࢡࢺࣝࡢ㓄ྥࢆṇ☜࡟Ỵᐃࡍࡿࡓࡵ࡟ࡣࠊ5ࡘࡢ⊂❧ࡋࡓ㓄ྥ᝟ሗࡀồࡵࡽࢀࡿࡀ [2]ࠊ☢ሙ㓄ྥ๣ࡢ✀㢮࡟ไ㝈ࡀ࠶ࡿࡇ࡜ࡸ㐺⏝᮲௳ࡢ㐪࠸ࡀ5ࡘࡢ㓄ྥ᝟ሗࢆᚓࡿୖ࡛㞀ᐖ࡟࡞ࡗ࡚࠸ࡿࠋࡼࡾከࡃࡢ㓄ྥ᝟ሗࢆᚓࡿࡓࡵࠊࡇࢀࡲ࡛࡟ከࡃࡢ☢ሙ㓄ྥ๣ࡀ
㛤Ⓨࡉࢀ࡚ࡁࡓࠋ㏆ᖺࠊ㓟໬ࢳࢱࣥࢼࣀࢩ࣮ࢺ(TiNSs)ࡀ☢ሙ࡟ᑐࡋ࡚ᆶ┤࡟㓄ྥࡍࡿࡇ࡜ࡀ☜ㄆࡉࢀࠊ☢ሙ㓄ྥ๣࡜ࡋ࡚ࡢ฼⏝ࡀ᳨ウࡉࢀ࡚࠸ࡿ [3-5]ࠋTiNSs୰ࡢ㔜ỈศᏊࡀ0-90 ႏࡢᖜᗈ࠸
ṧవ཮ᴟᏊ┦஫స⏝ࠊ㓟໬ࢳࢱࣥࢼࣀࢩ࣮ࢺࠊ㠀⏺㠃άᛶ๣ࢫࣝࣇ࢛࣋ࢱ࢖ࣥ
‫࠿ ࡘࡲ࠿ࢃࠊࡇࡦࡋ࡜ ࡁࡂࡍࠊࡇ࠺ࡻࡁ ࡓ࠸ࡿࡩࠊ࠸࠾࠶ ࡈ࠿ࡇࠊࡲ࠺ࡺ ࠿ࡉࡓ࠸ۑ‬࠾ࡾࠊ࠺ࡕࡔ ࡢࡾࡺࡁࠊ࠸ࡋࡔ ࡸࡍࡦࢁࠊ࠶࠸ࡔ ࡓࡃࡒ࠺ࠊࡩࡌࢃࡽ ࡜ࡋࡳࡕࠊࡇࡌࡲ
ࡕࡻ࠺ࡌࢁ࠺

－ 206 －

ᗘ⠊ᅖ࡟࡚ࠊ150 Hz⛬ࡢᴟࡵ࡚኱ࡁ࡞ᅄᴟᏊศ⿣ࢆ୚࠼ࡿࡇ࡜࠿ࡽࠊᚑ᮶ࡢ㓄ྥ๣࡟ẚ࡭ࠊᗈ࠸ᗘ⠊ᅖ࡛ࡼࡾ኱ࡁ࡞RDC್ࡀྲྀᚓ࡛ࡁࡿ࡜ᮇᚅࡉࢀ࡚࠸ࡿ [3-5]ࠋࡋ࠿ࡋࠊTiNSs࡟ࡣ⺮ⓑ㉁ࢆ
྾╔ࡍࡿᛶ㉁ࡀ࠶ࡾࠊ⡆౽࡟⺮ⓑ㉁ࡢRDCࢆ ᐃࡍࡿᡭἲࡣ▱ࡽࢀ࡚࠸࡞࠸ࠋᮏ◊✲࡛ࡣࠊ⺮ⓑ㉁ࡢᏳᐃ໬ຠᯝࡸྍ⁐໬ຠᯝࢆᣢࡘ㠀⏺㠃άᛶ๣ࢫࣝࣇ࢛࣋ࢱ࢖ࣥ(NDSB) [6] ࡟╔┠ࡋࠊTiNSs
ࢆ⏝࠸࡚⡆౽࡟⺮ⓑ㉁ࡢRDC್ࢆ ᐃࡍࡿᡭἲࢆ㛤Ⓨࡋࡓࡢ࡛ሗ࿌ࡍࡿࠋ࠙ᐇ㦂ࠚ኱⭠⳦Ⓨ⌧⣔࡟ࡼࡾࠊ15Nᶆ㆑ࡋࡓࣉࣟࢸ࢖ࣥG B1 ࢻ࣓࢖ࣥ(GB1)ࢆⓎ⌧࣭⢭〇ࡋࡓࠋ☢ሙ㓄ྥ
๣ TiNSs࡜⺮ⓑ㉁Ᏻᐃ໬๣ NDSB-195 (Fig. 1a)ࢆῧຍࡋࡓGB1ࢧࣥࣉࣝ࡟࠾࠸࡚ࠊ1H-15N IPAPHSQC

ᐃࠊ 1H-15N HSQC

ᐃࢆ⾜ࡗࡓࠋNDSB㢮࡛ࡣNMR࡛ࡢ฼⏝౛ࡀከࡃሗ࿌ࡉࢀ࡚࠸ࡿ

NDSB-195ࢆึࡵࠊNDSB-211ࠊ-221ࠊcholine-O-sulfate (COS)ࢆ౑⏝ࡋࠊNMR ᐃࢆ⾜ࡗࡓࠋIPAPHSQCࢫ࣌ࢡࢺࣝ࠿ࡽྲྀᚓࡋࡓRDC್ࡣࠊPALESࢯࣇࢺ࢙࢘࢔ [7] ࢆ⏝࠸࡚ィ⟬್࡜ࡢ┦㛵ࢆ☜ㄆࡋࠊ ᐃᡭἲࡢಙ㢗ᛶࢆ┦㛵ಀᩘ(R)࡜Q factor࡛ホ౯ࡋࡓࠋNMR ᐃࡣBruker AVANCE რ HD
500 MHzࡢ⿦⨨ࢆ౑⏝ࡋࠊ308 K࡛⾜ࡗࡓࠋ࠙⤖ᯝ࣭⪃ᐹࠚ
ձ TiNSs࡜࡜NDSB-195ࢆ
ࢆ⏝࠸ࡓRDC ᐃ
TiNSs࡟15Nᶆ㆑GB1ࢆΰྜࡋࡓ࡜ࡇࢁࠊ
࠸ࡃࡘ࠿ࡢṧᇶࡢࢩࢢࢼࣝࡀᾘኻࡋࡓࠋ
ࡑࡇ࡛TiNSs࡟NDSBࡢ1✀࡛࠶ࡿNDSB195ࢆຍ࠼15Nᶆ㆑GB1ࢆΰྜࡋࡓࠋ1.0 M
NDSB-195ඹᏑୗ࡛ࡣࢩࢢࢼࣝࡢᾘኻࡣ
ぢࡽࢀࡎࠊGB1ࡢRDC್ࡢỴᐃࡀྍ⬟࡛࠶ࡾࠊ ᐃ್࡜ィ⟬್ࡢRࡀ0.9௨ୖ࠿ࡘQ
factorࡀ0.2௨ୗ࡜㠀ᖖ࡟ᙉ࠸┦㛵ࡀᚓࡽࢀࡓ (Fig. 1b)ࠋࡉࡽ࡟ࠊHSQCࢫ࣌ࢡࢺࣝ
ࡣGB1ࡢࡳࡢࢫ࣌ࢡࢺࣝ࡜ࡼࡃ୍⮴ࡋ࡚࠾ࡾࠊ⺮ⓑ㉁ࡢᵓ㐀࡬ཬࡰࡍᙳ㡪ࡀᑠࡉ࠸ࡇ࡜ࡀศ࠿ࡗࡓ (Fig. 1c)ࠋࡇࢀࡽࡢ⤖ᯝ
ࡼࡾࠊNDSB-195ࢆΰࡐࡿࡔࡅ࡛ಙ㢗ᗘࡢ㧗࠸RDCࡀᚓࡽࢀࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ

Fig. 1. (a) Chemical structure of NDSB-195. (b)Correlation plot of measured and calculated RDCs.
(c) 1H-15N HSQC spectrum of GB1 with TiNSs and
NDSB-195.

NDSB-195௨እࡢNDSB㢮࡛࠶ࡿNDSB-211ࠊNDSB-221ࠊcholine-O-sulfate (COS)ࢆ⏝࠸ࠊNDSB195࡜ྠᵝ࡟RDC್ࢆỴᐃࡋࡓ࡜ࡇࢁࠊRࠊQ factor࡜ࡶ࡟㠀ᖖ࡟ᙉ࠸┦㛵ࡀᚓࡽࢀࡓ (Table 1)ࠋࡇࢀࡽࡣNDSB㢮ࡀTiNSsࢆ⏝࠸ࡓRDC ᐃ࡟᭷ຠ࡛࠶ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ
NDSB㢮ࡢ⃰ᗘࢆ1.0 M࡜2.5 M࡟ㄪ〇ࡋࠊHSQC ᐃࠊRDC ᐃࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊ2.5 M NDSB㢮ࢆΰྜࡋࡓGB1ࡢHSQCࢫ࣌ࢡࢺࣝୖ࡛ࠊ࣮ࣝࣉ㡿ᇦ࡟఩⨨ࡍࡿṧᇶࡢ㢧ⴭ࡞໬Ꮫࢩࣇࢺኚ໬ࡀ
ぢࡽࢀࡓࠋ୍᪉࡛ࠊPALES࡟ࡼࡿゎᯒࡣ஧ḟᵓ㐀࡟㝈ᐃࡋ࡚࠾ࡾࠊ1.0 M NDSB㢮ࡢ౑⏝᫬ࡼࡾࢃࡎ࠿࡟ຎࡿࡶࡢࡢࠊRࠊQ factor࡜ࡶ࡟ᙉ࠸┦㛵ࡀᚓࡽࢀࡓ (Table 1)ࠋ

－ 207 －ղ ࣓࢝ࢽࢬ࣒ゎᯒ࣭┦஫స⏝ࣔࢹࣝᮏᡭἲ࡛ࡣࠊTiNSs࡜NDSB-195ࢆే⏝ࡍࡿࡇ࡜࡛RDC ᐃࢆᐇ⾜ࡋࡓࡀࠊTiNSs࡜NDSB-195ࡀ
ࡑࢀࡒࢀGB1࡟࡝ࡢࡼ࠺࡞ᙳ㡪ࢆཬࡰࡍ࠿ㄪᰝࡋࡓࠋ
TiNSsࡢࡳࢆ౑⏝ࡋࡓ

ᐃ࡛ࡣࠊRDCᐃ್࡜ィ⟬್ࡢ┦㛵ࡀᙅࡃࠊHSQCࢫ࣌ࢡࢺࣝୖ࡟࡚ࠊ

E2ࢫࢺࣛࣥࢻࡢ⾲㠃ṧᇶࡸ࣮ࣝࣉࡢṧᇶ࡟࡚ࢩࢢࢼࣝࡀᾘኻࡋ࡚࠸ࡓࠋࡇࡢࢩࢢࢼࣝࡢᾘኻ࠿ࡽࠊ
GB1ࡢE2ࢫࢺࣛࣥࢻࡢ⾲㠃࡛TiNSs࡜┦஫స⏝ࢆᙧᡂࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ (Fig. 2a)ࠋᙅ࠸┦㛵ࡣࠊࡇࡢ┦஫స⏝࡟ࡼࡾࠊᑡ࡞ࡃ࡜ࡶ2ࡘ௨ୖࡢ㓄ྥ㍈ࡀᏑᅾࡋࡓࡓࡵࡔ࡜⪃࠼ࡽࢀࡿࠋࡲࡓࠊ
NDSB-195ࡢࡳࢆ౑⏝ࡋࡓ ᐃ࡛ࡣࠊHSQCࢫ࣌ࢡࢺࣝୖ࡛ࠊ㏆᥋ࡋࡓ㡿ᇦ࡟Ꮡᅾࡍࡿ3ࡘࡢṧᇶ࡛㢧ⴭ࡞໬Ꮫࢩࣇࢺኚ໬ࡀ☜ㄆࡉࢀࡓࠋࡇࢀࡽࡢ᝟ሗࢆᇶ࡟ࠊHADDOCK [8]࡟ࡼࡗ࡚GB1̿NDSB195」ྜయࡢࣔࢹࣝᵓ㐀ࢆᵓ⠏ࡋࡓ (Fig. 2b)ࠋࡇࡢᵝ࡟TiNSsࠊNDSB-195࡜ࡶ࡟༢⊂࡛౑⏝ࡋࡓ㝿࡟ࡣࠊGB1࡜ࡢ┦஫స⏝ࡢᏑᅾࡀ♧၀ࡉࢀࡓࠋ
TiNSs࡜NDSB-195ࢆྠ᫬࡟౑⏝ࡋࡓ

ᐃ࡛ࡣࠊHSQCࢫ࣌ࢡࢺࣝୖ࡛ࢩࢢࢼࣝࡢᾘኻࡀぢࡽࢀ࡞ࡃ࡞ࡾࠊGB1࡜TiNSsࡢ┦஫స⏝ࢆᢚไࡋࡓࡇ࡜ࡀ♧၀ࡉࢀࡓ (Fig. 2c)ࠋNDSB-195౑⏝᫬࡟ぢࡽࢀࡓ໬Ꮫࢩࣇࢺኚ໬ࡀᢚไࡉࢀ࡚࠸ࡿࡇ࡜࠿ࡽࠊNDSB-195ࡣTiNSs࡟྾╔ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀ
ࡿࠋNDSB-195ࢆῧຍࡍࡿࡇ࡜࡟ࡼࡗ࡚GB1࡜TiNSsࡢ┦஫స⏝ࡀᢚไࡉࢀࡓࡓࡵࠊRDCࡢᐃ್࡜ィ⟬್࡟㠀ᖖ࡟ᙉ࠸┦㛵ࡀᚓࡽࢀࡓ࡜⪃࠼ࡽࢀࡿࠋ

Fig. 2. Schematic illustration of intermolecular interactions between GB1, TiNSs, and NDSB195. (a) Interactions between GB1 and TiNSs. Interaction sites are shown by sphere
representation with residue name. (b) Interactions between GB1 and NDSB-195 mapped on
the HADDOCK-derived structural model of GB1 complex with NDSB-195. Interaction sites
are shown by sphere representation with residue name. (c) No interaction between GB1 andTiNSs in the presence of NDSB-195.

－ 208 －ճ ࢔ࣛ࢖࣓ࣥࢺࢸࣥࢯࣝࡢẚ㍑
TiNSsࡣ☢ሙ୰࡛ࠊ☢ሙ࡟ᑐࡋ࡚ᆶ┤࡟㓄ྥࡍࡿࡇ࡜ࡀ☜ㄆࡉࢀ࡚࠸ࡿ [5]ࠋRDC ᐃ࡟ᗈࡃ฼⏝ࡉࢀ࡚࠸ࡿ☢ሙ㓄ྥ๣ࡢPf1 phageࡸࣂ࢖ࢭࣝࡣ☢ሙ࡟ᑐࡋ࡚ᖹ⾜࡟㓄ྥࡋ࡚࠾ࡾࠊᆶ┤㓄ྥ࠿ࡘᗈࡃ฼⏝ࡉࢀ࡚࠸ࡿ☢ሙ㓄ྥ๣ࡣ࡯࡜ࢇ࡝࡞࠿ࡗࡓࠋTiNSsࡢᆶ┤㓄ྥ࡟ᑐࡋ࡚ࠊNDSB㢮ࡢῧຍ࡟క࠺ᙳ㡪ࡸᐇ㝿࡟ᆶ┤㓄ྥ࡛࠶ࡿ࠿ࢆㄪᰝࡍࡿࡓࡵࠊPALES࠿ࡽᚓࡽࢀࡓ࢔ࣛ࢖࣓ࣥࢺ
ࢸࣥࢯࣝࡢẚ㍑ࢆ⾜ࡗࡓ (Table 1)ࠋࡑࡢ⤖ᯝࠊ4✀ࡢNDSB㢮ࡢῧຍ࡛GB1ࡢ㓄ྥ࡟ኚ໬ࡣ⏕ࡌ࡚࠸࡞࠸ࡇ࡜ࠊᖹ⾜㓄ྥࡢPf1 phage࡜ẚ㍑ࡋ࡚Daࡢ➢ྕࡀ཯㌿ࡋ࡚࠸ࡿࡇ࡜࠿ࡽᆶ┤㓄ྥ࡛࠶ࡿࡇ࡜ࠊ࡞࡝ࡀ᫂ࡽ࠿࡜࡞ࡗࡓ [9]ࠋTable 1. Alignment tensors of GB1 by using various measurement methods

Da (Hz)Rhombicity

Euler angles

R

Q factor

TiNSs

-4.18

0.463

(130, 68, 214)

0.870

0.436

TiNSs+1.0 M NDSB-195

-4.97

0.439

(121, 81, 221)

0.970

0.167

TiNSs+1.0 M NDSB-211

-5.27

0.319

(119, 80, 223)

0.959

0.182

TiNSs+1.0 M NDSB-221

-5.21

0.440

(118, 82, 219)

0.974

0.158

TiNSs+1.0 M COS

-4.81

0.345

(116, 78, 227)

0.967

0.159

TiNSs+2.5 M NDSB-195

-5.37

0.543

(122, 81, 216)

0.945

0.264

TiNSs+2.5 M NDSB-211

-4.84

0.504

(124, 81, 221)

0.960

0.196

TiNSs+2.5 M NDSB-221

-5.72

0.584

(127, 93, 205)

0.951

0.249

TiNSs+2.5 M COS

-3.50

0.495

(118, 77, 225)

0.971

0.167

Pf1 phage

5.62

0.410

(118, 83, 219)

0.970

0.169

࠙⤖ㄽࠚ
ᮏ◊✲࡛ࡣࠊ㓟໬ࢳࢱࣥࢼࣀࢩ࣮ࢺࢆ⺮ⓑ㉁ࡢRDC

ᐃ࡬㐺⏝ࡍࡿࡓࡵࠊ㠀⏺㠃άᛶ๣ࢫࣝࣇ

࢛࣋ࢱ࢖ࣥࢆ⏝࠸ࡓࠋ㓟໬ࢳࢱࣥࢼࣀࢩ࣮ࢺ࡬ࡢ⺮ⓑ㉁ࡢ྾╔ࢆ㠀⏺㠃άᛶ๣ࢫࣝࣇ࢛࣋ࢱ࢖ࣥ
ࡀᢚไࡍࡿࡇ࡜࡛ࠊಙ㢗ᗘࡢ㧗࠸RDC್ࡀྲྀᚓ࡛ࡁࡿࠋᮏᡭἲࡣࠊᆶ┤㓄ྥࡢ☢ሙ㓄ྥ๣࠿ࡽᵓ
㐀᝟ሗࢆᚓࡿ᪂ࡓ࡞RDC ᐃᡭἲࡢ1ࡘ࡜ࡋ࡚ᮇᚅࡉࢀࡿࠋ

࠙ཧ⪃ᩥ⊩ࠚ
[1] N. Tjandra and A. Bax, Science (1997), 278, 1111-1114.
[2] J. Tolman and K. Ruan, Chemical Reviews (2006), 106, 1720-1736.
[3] N. Uchida et al., ➨ 56 ᅇ NMR ウㄽ఍ (2017), L2-1, 36-37.
[4] N. Uchida et al., ➨ 58 ᅇ NMR ウㄽ఍ (2019), L3-3, 102-103.
[5] N. Uchida et al., Japanese Patent No. 6792268 (2020).
[6] L. Xiang et al., Journal of Magnetic Resonance (2008), 194, 147-151.
[7] M. Zweckstetter, Nature Protocols (2008), 3, 679-690.
[8] G. van Zundert et al., Journal of Molecular Biology (2016), 428, 720-725.
[9] J. Lprieau et al., Journal of the American Chemical Society (2008), 130, 7536-7537.

－ 209 －

P33

Ș-ࢢࣝࢥࢩࢲ࣮ࢮ㜼ᐖ≀㉁ࢆྵࡴࢡ࣡ⴥࡢᢞ୚࡟ࡼࡿ࣐࢘ࢫ⭠ෆ⎔ቃ࡬ࡢᙳ㡪ࡢNMR࣓ࢱ࣑࣎ࣟࢡࢫゎᯒ‫Ⳁ⏑ۑ‬㸪✄ᮧ ຬ㞞㸪Ᏽ Ꮚ㇦㸪኱す⿱Ꮨ㸪⇃ᮌᗣ⿱㸪┦ἑᬛᗣ
1໭ᾏ㐨኱Ꮫ࣭኱Ꮫ㝔⏕࿨⛉Ꮫ㝔

NMR metabolomics of administration of mulberry leaves containing Į-glucosidase
inhibitors on the intestinal environment of mice‫ۑ‬Li Gan 1, Yuga Inamura 1, Zihao Song 1, Yuki Ohnishi 1, Yasuhiro Kumaki 1, Tomoyasu Aizawa 1
1 Graduate School of Life Science, Hokkaido University
Mulberry leaf is considered as a functional food in many Asian countries. Previous studies have reported
that the mulberry leaf shows anti-hyperglycemic, anti-oxidative, and anti-inflammatory effects. However,
the effect of mulberry leaf on fecal metabolites is poorly understood. In this study, we conducted nuclear
magnetic resonance-based metabolomics on control and mulberry leaf powder (MLP)-treated mouse feces
across 9 weeks of treatment to reveal the effect of MLP intake over a long period. Carbohydrates, aminoacids, and propionate were found to significantly (P < 0.01-0.05) alter upon MLP treatment. In the MLPtreated group, levels of glucose and all amino acids were lower after week 5, while maltose increased clearly
after week 5. Propionate was higher from week 1 to 4. These results may suggest that the gut microbiota ofmouse might be modulated gradually by continuous treatment with MLP. The study provides significant
insights into the effects of long-term intake of MLP and provides a basis for further investigation intherapeutic application of MLP.
 ࠙⥴ゝࠚ᪥ᮏࠊ୰ᅜࠊࢱ࢖ࢆྵࡴ࢔ࢪ࢔ㅖᅜ࡛᱂ᇵࡉࢀ࡚ࡁࡓࢡ࣡ࡢⴥ࡟ࡣ࣏ࣜࣇ࢙ࣀ࣮ࣝ➼ࡀከࡃྵࡲࢀ࡚࠾ࡾࠊᢠ⅖⑕స⏝➼ࡀሗ࿌ࡉࢀ࡚࠸ࡿ㸦P.Y. Chao, Evid. Based Complement.
Alternat. Med, 2013㸧ࠋࡲࡓࠊࢢࣝࢥ࣮ࢫ㢮ఝయ࡛࠶ࡿࢹ࢜࢟ࢩࣀࢪ࣐ࣜ࢖ࢩࣥ㸦DNJ㸧ࡀྵࡲࢀ࡚࠸ࡿࡇ࡜࠿ࡽࠊᙉຊ࡞Șࢢࣝࢥࢩࢲ࣮ࢮ㜼ᐖస⏝ࢆᣢࡘࡇ࡜ࡶ▱ࡽࢀ࡚࠸ࡿࠋ㐣ཤࡢ◊✲࡛ࡣ
DNJᢞ୚࡟ࡼࡿ⾑⢾್ࡢୖ᪼ᢚไࡸ࢖ࣥࢫࣜࣥ᢬ᢠᛶࡢᨵၿࡀሗ࿌ࡉࢀ࡚࠾ࡾ㸦Q. Liu,
Molecules, 2015㸧ࠊࢡ࣡ࡢⴥࡢᦤྲྀࡀ2ᆺ⢾ᒀ⑓ࡢண㜵᪉ἲ࡜ࡋ࡚ࡶὀ┠ࡉࢀࠊ◊✲ࡀከࡃᡂࡉࢀ
࡚࠸ࡿࠋࡋ࠿ࡋࠊࢡ࣡ⴥࡢᢞ୚᫬࡟኱ࡁࡃᙳ㡪ࢆཷࡅࡿ࡜᥎ᐃࡉࢀࡿ⭠ෆࡢ⣽⳦ྀࡸ௦ㅰ≀࡟㛵ࢃࡿ◊✲ࡣṤ࡝↓࠸ࠋ≉࡟⭠ෆ௦ㅰ≀ࡣᐟ୺࡜⭠ෆ⣽⳦ྀ࡜ࡢస⏝࡛⏕ࡌࠊᐟ୺࡟኱ࡁࡃᙳ㡪ࢆ
ཬࡰࡍⅭࠊࡑࡢ⥙⨶ⓗ࡞ゎᯒ࡛࠶ࡿ࣓ࢱ࣑࣎ࣟࢡࢫゎᯒࡢ᭷⏝ᛶࡣ㧗࠸࡜⪃࠼ࡽࢀࡿࠋࡑࡇ࡛ࠊ
ᮏ◊✲࡛ࡣヨᩱㄪ〇ࡀ⡆౽࡛࠶ࡾࠊ௦ㅰ≀ࡢᐃ㔞ᛶࡀ㧗࠸࡜࠸࠺≉ᚩࡀ࠶ࡿ᰾☢Ẽඹ㬆⿦⨨
㸦NMR㸧ࢆ⏝࠸ࡓ࣓ࢱ࣑࣎ࣟࢡࢫゎᯒ࡟ࡼࡾࠊ㛗ᮇ㛫ࢡ࣡ⴥ⢊ᮎࢆᢞ୚ࡋࡓC57BL/6࣐࢘ࢫࡢ⣅౽୰ࡢ௦ㅰ≀ࡢゎᯒࢆ⾜ࡗࡓࠋࢡ࣡ⴥ㸪࣓ࢱ࣑࣎ࣟࢡࢫ㸪࣐࢘ࢫ⣅‫ࡾ ࢇ࠿ۑ‬㸪࠸࡞ࡴࡽ ࡺ࠺ࡀ㸪ࡑࢇ ࡎࡣ࠾㸪࠾࠾࡟ࡋ ࡺ࠺ࡁ㸪ࡃࡲࡁ ࡸࡍࡦࢁ㸪࠶࠸ࡊࢃ ࡜ࡶࡸࡍ－ 210 －

࠙⤖ᯝ࣭⪃ᐹࠚ9㐌㛫࡟ࢃࡓࡾ1᪥2ᅇࠊ࣐࢘ࢫ࡟ࢡ࣡ⴥ⢊ᮎࢆᢞ୚ࡋࠊᑐ↷⩌࡜ࢡ࣡ⴥ⢊ᮎ(MLP)ᢞ୚⩌ࡢࡑࢀࡒࢀࡢ⣅౽࠿ࡽỈ⁐ᛶࡢ௦ㅰ≀ࢆᢳฟࡋࠊ
NMR ᐃࢆ⾜ࡗࡓ(Fig. 1)ࠋ
Chenomx NMR Suite 8.2 (ChenomxInc.)ࢆ⏝࠸࡚39✀ࡢ௦ㅰ≀ࡢྠᐃ࣭ᐃ㔞࡟ᡂຌࡋࡓࠋ୺࡞ᡂศ
ࡣⅣỈ໬≀㸦ࢢࣝࢥ࣮ࢫࠊ࣐ࣝ
ࢺ࣮ࢫࠊ࢞ࣛࢡࢺ࣮ࢫ㸧ࠊ࢔࣑

Fig. 1. 1H NMR spectra of mouse fecal extraction obtained
from control (A), MLP-treated (B).

ࣀ㓟㸦࢔ࣛࢽࣥࠊBCAAࠊࢢࣝࢱ࣑ࣥࠊࢢࣜࢩࣥ➼㸧ࠊ᭷ᶵ㓟㸦㓗㓟ࠊࣉࣟࣆ࢜ࣥ㓟ࠊ㓑㓟➼㸧࡛࠶ࡗࡓࠋ࣐ࣝࢺ࣮ࢫࡣᢞ୚㛤ጞ┤ᚋࡢ1㐌┠࠿ࡽMLPᢞ୚⩌ࡢࡳ࡛ቑຍࡋࠊ5㐌┠࡛᭱኱࡜࡞ࡗ
ࡓ㸦Fig. 2㸧ࠋࡇࢀ࡟ᑐࡋ࡚ࢢࣝࢥ࣮ࢫࡣ5㐌┠௨㝆࡛ῶᑡഴྥࡀぢࡽࢀࡓࠋࡇࢀࡽࡢ⤖ᯝࡣࢡ࣡ⴥ࡟ྵࡲࢀࡿȘ-ࢢࣝࢥࢩࢲ࣮ࢮ㸦࣐ࣝࢱ࣮ࢮ㸧㜼ᐖస⏝ࢆᣢࡘDNJࡢຠᯝࡀᢞ୚┤ᚋ࠿ࡽᚎࠎ࡟
⌧ࢀࠊ5㐌┠௨㝆࡛㢧ⴭ࡟ຠᯝࡀ⌧ࢀࡓ஦ࢆ♧၀ࡋ࡚࠸ࡿࠋࡲࡓࠊ࣐ࣝࢺ࣮ࢫࡣ5㐌┠௨㝆ῶᑡഴྥࡀࡳࡽࢀࡿࡇ࡜࠿ࡽࠊ⭠ෆ⣽⳦ྀ࡟࣐ࣝࢺ࣮ࢫ฼⏝ᛶࡢ⳦ࡀቑຍࡋ࡚࠸ࡿྍ⬟ᛶࡀ♧၀ࡉࢀࡓࠋ࢔࣑ࣀ㓟ࡣ୧⩌࡛࡝ࡕࡽࡶῶᑡഴྥ࡟࠶ࡗࡓࡀࠊ5㐌┠௨㝆࡛ࡣMLPᢞ୚⩌ࡢ඲࡚ࡢ࢔࣑ࣀ
㓟ࡀᑐ↷⩌ࡼࡾ᫂ࡽ࠿࡟ῶᑡࡋࡣࡌࡵࡓࠋࡇࢀࡽࡢ⤖ᯝ࠿ࡽࠊ5㐌㛫௨ୖࡢᢞ୚࡟ࡼࡾᐟ୺ࡸ⭠ෆ⣽⳦ྀ࡟ࡼࡿ⺮ⓑ㉁ࡢศゎࡸ࢔࣑ࣀ㓟ࡢྲྀࡾ㎸ࡳࡀኚ໬ࡋࡓ࡜᥎ᐃࡉࢀࡿࠋ᭷ᶵ㓟࡟ࡘ࠸࡚ࡣ
TCAᅇ㊰௦ㅰ≀㸦ࢥࣁࢡ㓟ࠊࣇ࣐ࣝ㓟㸧ࢆྵࡵ࡚ࠊṤ࡝ኚ໬ࡀぢࡽࢀ࡞࠿ࡗࡓࠋࡇࢀࡽࡢ⤖ᯝࢆ⥲ᣓࡍࡿ࡜ࠊ⥅⥆ⓗ࡞ࢡ࣡ⴥࡢᦤྲྀࡣ⭠ෆ⣽⳦ྀ࡟ᙳ㡪ࢆ୚࠼ࡿࡇ࡜࡛ࠊ⭠ෆ௦ㅰ≀ࢆኚ໬ࡉࡏࠊ⭠ෆ⎔ቃ࡟ᙳ㡪ࢆ୚࠼ࡿྍ⬟ᛶࡀ♧၀ࡉࢀࡓࠋ௒ᚋࡣᐟ୺⤌⧊ࢆᑐ㇟࡟ࡋࡓNMR࣓ࢱ࣑࣎ࣟࢡࢫゎᯒࡶ⾜࠺ணᐃ࡛࠶ࡿࠋ

Fig. 2. Time course quantitative values of control (dotted line) and MLP-treated (solid line) mouse
feces. Values are mean ± SEM. Asterisk indicates significant difference between control and MLPtreated (*P < 0.05, **P < 0.01)－ 211 －

P34Y

105DQDO\VLVRIbIXFRV\OODFWRVHLQKXPDQEUHDVWPLON‫▱⬌ۑ‬ᙪ㸪ⵓె⛥㸪⏑Ⳁ㸪ᏵᏊ㇦㸪኱す⿱Ꮨ㸪㛗⏣ㄔྖ㸪ஂ⡿⏣༤அ㸪⇃ᮌᗣ⿱㸪ᒣෆ୍ኵ㸪┦ἑᬛᗣ໭኱࣭㝔⏕࿨⛉Ꮫ୰ᒣၟ஦㸦ᰴ㸧Ἀ⦖⛉Ꮫᢏ⾡኱Ꮫ㝔኱Ꮫ ᶵჾศᯒࢭࢡࢩࣙࣥ

NMR analysis of 2’-fucosyllactose in human breast milk‫ۑ‬Zhiyan Hu1, Jiaxi Jiang1, Li Gan1, Zihao Song1, Yuki Ohnishi1, Seiji Osada2, Hiroyuki Kumeta1,
Yasuhiro Kumaki1, Kazuo Yamauchi3, Tomoyasu Aizawa1,
1 Grad. Sch. Life Sci., Univ. Hokkaido
2Nakayama Co.,Ltd.

3 Instrumental Analysis Section, OISTHuman breast milk (HBM) is the primary source of newborn infants. 2’-fucosyllactose (2’-FL) and 3fucosyllactose (3-FL) are the main components in human milk oligosaccharides (HMOs), which facilitate
gut integrity and benefit for brain. The secretion of 2’-FL relates to the FUT2 gene, which encodes the Į(1,2)-fucosyltransferase. Another FUT2 gene-related HMO is lacto-N-fucopentaose I (LNFP- I), while 3-FL
is not related. Mothers who can produce the enzyme are regarded as secretors, otherwise as non-secretors. In
this study we investigated a new technique to analyze these HMOs in HBM using a 60 MHz low-fieldbenchtop NMR spectrometer. By analyzing peaks from methyl groups in fucose, we succeeded in clearly
distinguishing between secreted and non-secreted donors using a 60 MHz NMR system. Furthermore, we
succeeded in obtaining quantitative results for HMO that correlated well with a superconducting high-field
NMR system.
Introduction
2’-FL promotes immune development in the gut
in a child’s early years and helps infants suffer fromless upper respiratory tract infections. 3-FL could
reduce the risk of gut microbiota imbalance caused
by undesirable harmful bacteria.
The secretion of 2’-FL and LNFP-I depends on
the

FUT2

gene,

which

encodes

Į-(1,

2)-

fucosyltransferase. This enzyme catalyzes the
addition of fucose to HMOs, and the mother isreferred to as secretory or nonsecretory dependingon the presence or absence of its enzyme synthesis

Fig. 1 800 MHz and 60 MHz 1H NMR spectra ofa representative HBM sample.
60 MHz NMR shown upper, 800 MHz shown lower.

capacity. Determining which group a mother falls into may be clinically meaningful.
Benchtop NMR, 2’-FL, Human milk oligosaccharides‫ࢇࡆࡋ ࡇۑ‬㸪ࡋࡻ࠺ ࠿ࡁ, ࠿ࢇ ࡾ㸪ࡑࢇ ࡎࡣ࠾㸪࠾࠾࡟ࡋ ࡺ࠺ࡁ㸪࠾ࡉࡔ ࡏ࠸ࡌ㸪ࡃࡵࡓ ࡦࢁࡺࡁ㸪ࡃࡲࡁ ࡸࡍࡦࢁ㸪ࡸࡲ࠺ࡕ ࠿ࡎ࠾㸪࠶࠸ࡊࢃ ࡜ࡶࡸࡍ－ 212 －

In this study, we applied a method for quantifying HMOs in HBM using NMR spectroscopy, particularly
a benchtop NMR spectrometer with a permanent magnet . NMR spectrometers that high-field NMR
spectrometers using superconducting magnets have been conventionally used for the analysis of HMOs,
which have the advantage of high sensitivity, high resolution. However, its large size and maintenance suchas refrigerant supply do not suit clinical use in hospitals and nursing care facilities. Thus, simpler and lessexpensive devices such as benchtop NMR spectrometers are expected to be available. We used a 60 MHz
benchtop NMR system to determine the presence or absence of 2'-FL and other HMOs. We report on the
results of the determination of the presence or absence of HMOs, including 2’-FL, and their quantitativetechniqueds using a 60 MHz benchtop NMR system.
Results and discussion
Thirty-seven samples of HBM
who were hospitalized immediately
after delivery were analyzed by
NMR, of which are in Fig. 1 shown
the representative example. The
used detection region for both 800
MHz and 60 MHz were the signals

CONCENTRATION (mM)obtained from 37 sample donors



800 MHz

60 MHz






21 6 32173029 3 20241931 8 1637 2 23362725123315113528 5 222618 1 7 4 9 13341410

SAMPLE NUMBER

from the methyl group for fucosyl Fig. 2 The concentration of 2’-FL quantified by 800 MHz and 60
unit. For 800 MHz NMR, the peaks
MHz.
of 2’-FL, 3-FL, and LNFP-I were
Quantification result of 60 MHz shown the same result of
1.249-1.222 ppm, 1.211-1.179
distinguishment of secretor status as 800 MHz.
ppm,
1.255-1.231
ppm,
respectively. For 60 MHz benchtop NMR, the peaks of 2’-FL, 3-FL, and LNFP-I were 1.37-1.07 ppm, 1.321.05 ppm, 1.39-1.08 ppm.
Quantitative analysis of each HMO was performed using Chenomx software. Standard sample solutionsof each HMO were prepared and an in-house database for 800 MHz and 60 MHz NMR spectra wasconstructed. Then, the peaks in the methyl region were separated by manual fitting operations, andquantitative analysis of each HMO was performed. For 2’-FL detected by 800 MHz, sample numbers 7, 4,
13, 34, 9, 14, 10 showed quite low level of concentration of 2’-FL (Fig.2), less than 0.5 mM. For the other30 samples, the concentration was between 30 and 5 mM. It was easy to distinguish the secretor and nonsecretor status.
For 2’-FL detected at 60 MHz, the determination of secretor or not was like that at 800 MHz, with 7
samples being non-secretor and 30 samples being secretor. For LNFP-I, clear discrimination between secretor
and non-secretors was possible, even though its absolute concentration was much lower than that of 2’-FL.
3-FL showed a negative correlation compared with the concentration trends of 2’-FL and LNFP-I. Although
the enzyme responsible for 3-FL is different from 2’-FL and LNFP-I, its synthetic substrate is common,suggesting that competition may be occurring in the synthetic process.
Comparing the concentration detected by 800 MHz and 60 MHz, all the three HMOs showed a linear
positive correlation between 800 MHz and 60 MHz. These results indicated that 60 MHz benchtop NMR canbe applied as a bedside diagnostic technique that can quantify HMOs as well as whether the maternity.

－ 213 －

P35

ࢼࣀࢲ࢖ࣖࣔࣥࢻࢆศᴟ๣࡜ࡋ࡚⏝࠸ࡓDNP-MAS-NMRࡢ⏕యศᏊ࡬ࡢᛂ⏝‫ۑ‬ຍ⸨㈼㸪⏣ᕳึ㸪ᮡୗ཭᫭㸪⸨ཎᩄ㐨㸪ᯇᮌ㝧
1 ኱㜰኱Ꮫ ⺮ⓑ㉁◊✲ᡤ
2 ኱㜰኱Ꮫ 㔞Ꮚ᝟ሗ࣭㔞Ꮚ⏕࿨◊✲ࢭࣥࢱ࣮

Application of nanodiamond-based polarizing agent for DNP-MAS-NMR to biomolecules‫ۑ‬Ken Kato1, Hajime Tamaki1, Tomoaki Sugishita1, Toshimichi Fujiwara1,2, Yoh Matsuki1,2
1Institute for Protein Research, Osaka University

2

Center for Quantum Information and Quantum Biology, Osaka University
Dynamic nuclear polarization (DNP)-NMR is a method for enhancing the NMR signal intensity bytransferring the polarization from the electron spin to the nuclear spin. The organic radicals such as nitroxide
radical are widely used in DNP polarizing agent. However, nitroxide-based polarizing agent rapidly degraded
due to the strongly reducing environment such as in-cell condition. Novel DNP polarizing agents with highreduction resistance are required. Nanometer scale diamond particles have a lot of unpaired electrons fromsurface dangling bonds. These unpaired electrons on nanodiamond are expected to be used as DNP polarizing
agent in reduction condition due to their high chemical/physical stability. However, it has not been reported
that DNP-NMR measurements of biomolecule with nanodiamond-based polarizing agent under highmagnetic field and magic angle spinning (MAS) conditions yet. In this presentation, we will report of ESR
and DNP-MAS-NMR measurement of nanodiamond in reduction condition and its application to proteins.
ືⓗ᰾ศᴟ㸦DNP㸧-NMRἲࡣࠊ☢Ẽᅇ㌿ẚࡢ኱ࡁ࠸㟁Ꮚࢫࣆࣥࡢ⇕ศᴟࢆ᰾ࢫࣆࣥ࡟⛣ࡍࡇ࡜
࡟ࡼࡾNMRࢆ㧗ឤᗘ࡟ ᐃࡍࡿᡭἲ࡛࠶ࡿࠋDNPࡢศᴟ๣࡟ࡣࢽࢺࣟ࢟ࢩࢻࣛࢪ࢝ࣝ࡟௦⾲ࡉࢀࡿࡼ࠺࡞᭷ᶵࣛࢪ࢝ࣝࡀᗈࡃ౑ࢃࢀ࡚࠸ࡿࡀࠊࡑࡢ཯ᛂᛶࡢ㧗ࡉ࠿ࡽ౛࠼ࡤ⣽⬊ෆ࡜࠸ࡗࡓ㑏ඖⓗ⎔ቃ࡛ࡣࣛࢪ࢝ࣝࡀ⣲᪩ࡃኻάࡍࡿ࡜࠸ࡗࡓၥ㢟ࡀ࠶ࡾ1ࠊ⪏㑏ඖᛶࢆ᭷ࡍࡿศᴟ๣ࡢ㛤Ⓨࡀᮃࡲࢀ࡚࠸ࡿࠋࢼࣀࢲ࢖ࣖࣔࣥࢻࡣ⏕య㐺ྜᛶࡀ㧗࠸ࢼࣀᮦᩱ࡜ࡋ࡚ࠊ⣽⬊ෆࡢࣜ࢔ࣝࢱ࢖࣒ィࡀྍ⬟࡞⺯ගࣉ࣮ࣟࣈࡸ ᗘ㸭pHࢭࣥࢧ࣮࡬ࡢᛂ⏝ࢆ┠ᣦࡋࡓ◊✲ࡀ┒ࢇ࡟⾜ࢃࢀ࡚࠸ࡿࠋࢼࣀ
࣓࣮ࢺࣝࢫࢣ࣮ࣝࡢࢲ࢖ࣖࣔࣥࢻ⢏Ꮚࡣẚ⾲㠃✚ࡀ኱ࡁ࠸ࡓࡵࠊ⾲㠃ࢲࣥࢢࣜࣥࢢ࣎ࣥࢻ࡟⏤᮶ࡍࡿከᩘࡢ୙ᑐ㟁Ꮚࢆ᭷ࡋ࡚࠾ࡾࠊࡑࡢ୙ᑐ㟁Ꮚࢆศᴟ※࡜ࡋ࡚ࢲ࢖ࣖࣔࣥࢻෆ㒊ࡢኳ↛Ꮡᅾẚ
ࡢ13Cࡸ࿘ᅖ⁐፹ࡢ1HࡢNMRಙྕࢆቑᙉࡋࡓ౛ࡀሗ࿌ࡉࢀ࡚࠸ࡿ2ࠋࢼࣀࢲ࢖ࣖࣔࣥࢻࡢࢲࣥࢢࣜ
ࣥࢢ࣎ࣥࢻࡢ୙ᑐ㟁Ꮚࡣ㧗࠸໬Ꮫⓗ㸭≀⌮ⓗᏳᐃᛶࢆ᭷ࡍࡿࡓࡵ⣽⬊⎔ቃෆ࡟࠾࠸࡚ࡶDNPศᴟ
๣࡜ࡋ࡚ࡢ฼⏝ྍ⬟ࡔ࡜ᮇᚅࡉࢀࡿࡀࠊ
ᵓ㐀ゎᯒࢆᚿྥࡋࡓ㧗☢ሙ࠿ࡘ࣐ࢪࢵࢡゅヨᩱᅇ㌿㸦MAS㸧᮲௳࡛ࡢ⏕యศᏊࡢDNP-NMR ᐃ౛ࡣሗ࿌ࡉࢀ࡚࠸࡞࠸ࠋᮏⓎ⾲࡛ࡣࢼࣀࢲ࢖ࣖࣔࣥࢻศᴟ๣ࡢ
⏕య฼⏝ࢆ┠ᣦࡋ࡚ࠊESRᐃ࡟ࡼࡿࢼࣀࢲ࢖ࣖࣔࣥࢻࡢ㟁Ꮚࢫࣆࣥࡢ⪏㑏ඖᛶࡢ᳨ド࡜㑏ඖ๣Ꮡᅾୗ࡟࠾ࡅࡿࢼࣀࢲ࢖ࣖࣔࣥࢻศᴟ๣ࢆ⏝࠸ࡓDNP-MAS-NMR ᐃࠊ࠾ࡼࡧࢼࣀࢲ࢖ࣖࣔࣥࢻ
ศᴟ๣ࢆ⏝࠸ࡓࢱࣥࣃࢡ㉁ࡢNMRಙྕࡢቑᙉࡢヨࡳ࡟ࡘ࠸࡚ሗ࿌ࡍࡿࠋ

DNP-MAS-NMR㸪ศᴟ๣㛤Ⓨ㸪ࢼࣀࢲ࢖ࣖࣔࣥࢻ
‫ࢇࡅ࠺࡜࠿ۑ‬㸪ࡓࡲࡁࡣࡌࡵ㸪ࡍࡂࡋࡓ࡜ࡶ࠶ࡁ㸪ࡩࡌࢃࡽ࡜ࡋࡳࡕ㸪ࡲࡘࡁࡼ࠺

－ 214 －

࢔ࢫࢥࣝࣅࣥ㓟Ꮡᅾୗ࡛ࡢTEMPOLࣛࢪ࢝ࣝ࡜

4000ࢼࣀࢲ࢖ࣖࣔࣥࢻࡢESRࢫ࣌ࢡࢺࣝ࡜ࡑࡢ᫬㛫ኚ
໬ࢆFig. 1࡟♧ࡍࠋ࢔ࢫࢥࣝࣅࣥ㓟㑏ඖ⎔ቃ࡛ࡣࢽ࢔ࢫࢥࣝࣅࣥ㓟⃰ᗘࡀ100ಸ㧗࠸⎔ቃ࡟࠾࠸࡚ࡶ
ࢼࣀࢲ࢖ࣖࣔࣥࢻࡢESRಙྕࡣኻάࡋ࡞ࡗࡓࠋࡲ

Intensity / a.u.

ࢺࣟ࢟ࢩࢻࡢESRಙྕࡣ20ศ࡯࡝࡛ῶ⾶ࡋࡓࡀࠊ3000ࡓࠊࢢࣝࢱࢳ࢜ࣥᏑᅾୗ࠾ࡼࡧ኱⭠⳦ࣛ࢖ࢭ࣮ࢺ

(a)

1000
336

Ꮡᅾୗ࡛ࡣTEMPOLࣛࢪ࢝ࣝࡢESRಙྕࡢῶ⾶ࡀ
ほ

0

0

30

άࡏࡎࠊ㧗࠸⪏㑏ඖᛶࢆ᭷ࡍࡿࡇ࡜ࡀ᫂ࡽ࠿࡟࡞
࡚⏝࠸࡚ࠊ࢔ࢫࢥࣝࣅࣥ㓟Ꮡᅾୗ࡛ࢢࣜࢭ࣮ࣟࣝ
ࡢ13C-DNP-NMR ᐃࢆ⾜ࡗࡓࠋDNP-MAS-NMRᐃࡣᡤᒓ◊✲ᐊ࡛㛤Ⓨࡉࢀࡓ㛢ᅇ㊰࣒࣊ࣜ࢘࢞ࢫ
MAS-DNPࣉ࣮ࣟࣈࢩࢫࢸ࣒3ࢆ౑⏝ࡋࠊ㟼☢ሙB0 =16.4 TࠊMAS㏿ᗘȞR = 5 kHzࠊ ᗘT = 30 Kࡢ᮲௳࡛ࠊ┤ᚄ‫ = ׋‬3.2 mm࣮ࣟࢱ࣮ࢆ⏝࠸࡚ᐇ㦂ࢆ⾜ࡗ

338

340

342

344

346

348

336

Magnetic Field / mTࡉࢀࡓࡀࠊࢼࣀࢲ࢖ࣖࣔࣥࢻࡢESRಙྕࡣኻࡗࡓࠋࡲࡓࠊࢼࣀࢲ࢖ࣖࣔࣥࢻࢆDNPศᴟ๣࡜ࡋ

(b)

2000

60

338

340

342

344

346

348

Magnetic Field / mT

90

120

150

Time / minFig. 1. Decay profiles of the ESR spectral
intensity of TEMPOL (black) and nanodiamond(gray) at room temperature in the ascorbate
solution. (Insert; a) Typical ESR spectrum of
TEMPOL. (Insert; b) Typical ESR spectrum of
nanodiamond water dispersion.

ࡓࠋ㟁Ꮚࢫࣆࣥࢆບ㉳ࡍࡿȞ = 460 GHzࡢࢧࣈ࣑ࣜἼ↷ᑕ࡟ࡼࡗ࡚ࠊࢢࣜࢭ࣮ࣟࣝ࡜ࢲ࢖ࣖࣔࣥࢻ
ෆࡢ13CⅣ⣲ࡢNMRಙྕࡢቑᙉࡀほᵝࡢಙྕࡢቑᙉࡀほࡉࢀࡓࠋ࠸ࡎࢀࡢNMRಙྕࡶ࢔ࢫࢥࣝࣅࣥ㓟ඹᏑୗ࡛ࡶྠ

ࡉࢀࠊ㑏ඖⓗ⎔ቃୗ࡟࠾࠸࡚ࡶࢼࣀࢲ࢖ࣖࣔࣥࢻࡢ⾲㠃㟁ᏊࢆDNPศᴟ๣࡜ࡋ࡚฼⏝࡛ࡁࡿࡇ࡜ࡀ♧ࡉࢀ(a)ࡓࠋ

Protein
DNP enhancement regionࡲࡓࠊࢼࣀࢲ࢖ࣖࣔࣥࢻ⾲㠃ࡢ໬Ꮫಟ㣭࡟ࡼࡗ࡚ྠ఩యᶆ㆑

Nanodiamond

ChemicalSynthesisࡋࡓࣔࢹࣝࢱࣥࣃࢡ㉁࡜⤖ྜࡋࡓ⣔㸦Fig. 2a㸧ࡸࣜ࢞ࣥࢻࢆ௓ࡋ
࡚࢔࣑ࣟ࢖ࢻ⥺⥔࡟≉␗ⓗ࡟⤖(b)Ligandྜࡋࡓ⣔㸦Fig. 2b㸧࡟࠾࠸࡚ࡶ
DNP-MAS-NMRᐃ࡟ࡼࡿ㑅ᢥ

ⓗ࡞ಙྕࡢቑᙉࢆヨࡳ࡚࠸ࡿࠋࡇࢀࡽࡢヲ⣽ࡣᙜ᪥ࠊウㄽࡍࡿணᐃ࡛࠶ࡿࠋ

ChemicalSynthesis

Nanodiamond
Amyloid Fibril

Fig. 2. Schematic diagram of nanodiamond binding protein (a), andamyloid fibril (b).

References(1) M. Azarkh, O. Okle, P. Eyring, D. R. Dietrich, M. Drescher, J. Magn. Reson. 212, 450–454 (2011).; K. M.
McCoy, R. Rogawski, O. Stovicek, A. E. McDermott, J. Magn. Reson. 303, 115–120 (2019).; R. Ghosh, R.
Dumarieh, Y. Xiao, K. K Frederick, J. Magn. Reson. 336, 107150 (2022).
(2) E. Rej, T. Gaebel, T. Boele, D. E. J. Waddington, D. J. Reilly, Nat. Commun. 6, 8459 (2015).; C. O.
Bretschneider, Ü. Akbey, F. Aussenac, G. L. Olsen, A. Feintuch, H. Oschkinat, L. Frydman, ChemPhysChem
17, 2691–2701 (2016).; E. Rej, T. Gaebel, D. E. J. Waddington, D. J. Reilly, J. Am. Chem. Soc. 139, 193í199(2017).
(3) Y. Matsuki, S. Nakamura, S. Fukui, H. Suematsu, T. Fujiwara, J. Magn. Reson. 259, 76í81 (2015).; Y. Matsuki,
S. Nakamura, T. Idehara, J. Fukazawa, T. Fujiwara, J. Magn. Reson. 264, 107í115 (2016).; Y. Matsuki, S.
Nakamura, F. Hobo, Y. Endo, H. Takahashi, H. Suematsu, T. Fujiwara, J. Magn. Reson. 335, 107139 (2022).

－ 215 －

P36Y

᫬㛫㡿ᇦNMRࢆ⏝࠸ࡓ⏕ศゎᛶᮦᩱࡢ㐠ືᛶ࣭ぶỈᛶホ౯࡟ᇶ࡙ࡃ⤌ᡂ᭱㐺໬
‫ۑ‬ᒣ⏣㞙Ⴙ㸪ᆤ஭⿱⌮㸪⳥ᆅ῟
1⌮໬Ꮫ◊✲ᡤ࣭⎔ቃ㈨※⛉Ꮫ◊✲ࢭࣥࢱ࣮
2ᶓ὾ᕷ❧኱Ꮫ኱Ꮫ㝔࣭⏕࿨་⛉Ꮫ◊✲⛉3ྡྂᒇ኱Ꮫ኱Ꮫ㝔࣭⏕࿨㎰Ꮫ◊✲⛉Composition optimization based on water-immobility evaluation of biodegradable
materials using time-domain NMR‫ۑ‬Shunji Yamada1, Yuuri Tsuboi1, Jun Kikuchi1,2,3
1 RIKEN Center for Sustainable Resource Science
2 Graduate School of Medical Life Science, Yokohama City University
3 Graduate School of Bioagricultural Sciences, Nagoya University

As the sustainability of the global environment is emphasized, the development of environment-friendly
materials, such as dealing with the problem of marine plastics, is flourishing. The material parameter spaceis huge, and efficient search is an issue. Time-domain NMR (TD-NMR) provides material property
information via the complex T2 relaxation curves resulting from multiple mobility. In this study, we used
TD-NMR to evaluate the binding state of water (water-immobility) in oligomer synthesized with various
monomer compositions immersed in seawater. We acquired NMR data using various pulse sequences suchas magic sandwich echo (MSE), double quantum filter (DQ), magic and polarization echo (MAPE) and
Carr-Purcell-Meiboom-Gill (CPMG). The T2 relaxation curves were separated into two components, waterbound oligomers, and free water. Machine learning methods such as random forest, generative topography
mapping regression and Bayesian optimization can explore oligomers with desired water-immobility.
1㸬㸬⫼ᬒ࣭┠ⓗᆅ⌫⎔ቃࡢᣢ⥆ྍ⬟ᛶࡀ㔜どࡉࢀࡿ୰ࠊᾏὒࣉࣛࢫࢳࢵࢡၥ㢟࡬ࡢᑐฎ࡞࡝⎔ቃ㓄៖ᆺᮦᩱ㛤Ⓨࡀ┒ࢇ࡛࠶ࡿ[1]ࠋᮦᩱࣃ࣓࣮ࣛࢱ✵㛫ࡣ⭾኱࡛࠶ࡾࠊ᥈⣴ࡢຠ⋡໬ࡀㄢ㢟࡛࠶ࡿࠋ᫬㛫㡿ᇦNMR(TD-NMR)ࡣࠊT2⦆࿴᫬㛫࡟ࡼࡾ」ᩘࡢ㐠ືᛶ࡟⏤᮶ࡍࡿ」ྜⓗ࡞ಙྕࢆᥦ౪ࡍࡿ[2,3]ࠋ௨
๓ࡢ◊✲࡛ࡣࠊ㨶⫗୰ࡢ⤖ྜỈ࡜⮬⏤Ỉࡢ≉ᛶ࡟ࡘ࠸࡚TD-NMRࡢ⦆࿴᭤⥺ࡢᶵᲔᏛ⩦ࡀ᭷ຠ࡛࠶ࡗࡓ[4]ࠋᮏ◊✲࡛ࡣࠊࣔࣀ࣐࣮⤌ᡂࢆኚ࠼ࡓᵝࠎ࡞࢜ࣜࢦ࣐࣮ࢆ⏝࠸࡚ࠊ࢜ࣜࢦ࣐࣮ࢆᾏỈ࡟ᾐࡍࡇ࡜࡛㐠ືᛶ࣭ぶỈᛶ᝟ሗࢆホ౯ࡋࡓ(Fig.1)ࠋSolid-EchoࠊMagic sandwich echo (MSE)ࠊ
Double quantum filter (DQ)ࠊMagic and polarization echo (MAPE)ࠊCarr-Purcell-Meiboom-Gill (CPMG)࡞࡝ྛ✀ࣃࣝࢫ⣔ิࡢNMRࢹ࣮ࢱࢆྲྀᚓࡋࠊT2⦆࿴᫬㛫࠿ࡽ࢜ࣜࢦ࣐࣮ࡢỈ୙ືᛶࠊ⮬⏤Ỉࡢ๭ྜࢆ⟬ฟࡋࡓࠋT2⦆࿴᫬㛫࠿ࡽᚓࡿỈ୙ືᛶᣦᶆࢆ⏝࠸࡚ࠊ㧗࠸Ỉ୙ືᛶࢆᣢࡘ࢜ࣜࢦ࣐࣮⤌ᡂࢆ᥈⣴ࡋࡓࠋ㧗Ỉ୙ືᛶࢆᣢࡘ࢜ࣜࢦ࣐࣮ࡢ㔜せᅉᏊ᥈⣴ࢆࡍࡿࡓࡵ࡟ࠊࣛࣥࢲ࣒ࣇ࢛ࣞࢫࢺ(RF) [5]ࠊGenerative topography mapping regression (GTMR)[6]ࢆ⏝࠸ࠊ⤌ᡂೃ⿵࠿ࡽ㧗࠸Ỉ୙ືᛶࢆᣢࡘྍ⬟ᛶࡀ㧗࠸ೃ⿵ࢆண ࡍࡿࡓࡵ࡟Bayesian optimization (BO)[7]ࢆ㐺⏝ࡋࡓࠋ

T2⦆࿴᫬㛫㸪⏕ศゎᛶᮦᩱ㸪⤌ྜࡏ᭱㐺໬‫ࡌࢇࡹࡋࡔࡲࡸۑ‬㸪ࡘࡰ࠸ࡺ࠺ࡾ㸪ࡁࡃࡕࡌࡹࢇ

－ 216 －

Fig. 1. Oligomer composition optimization with desired water-immobility using time-domain NMR.
(a) MSE, DQ, MAPE and CPMG data were acquired by time-domain NMR. (b) T2 relaxation times wereseparated based on the mobility and water-immobility of oligomers. (c) Random forest and GTMR wereused to search for important factors from molecular weights, terminal ratios, and molecular descriptors forwater immobility, and Bayesian optimization was used to optimize compositions.
2㸬
㸬᪉ἲ
2.1㸬
㸬ࢧࣥࣉࣝ‽ഛ࢜ ࣜ ࢦ࣐ ࣮ ᮦ ᩱࡣ ࠊ 14✀ 㢮 ࡢ ࣔ ࣀ ࣐ ࣮࠿ ࡽ ࠊ2ࡘ ࡲ ࡓ ࡣ 3ࡘ ࡢ ࣔ ࣀ࣐࣮ ࢆ ⤌ࡳ ྜࢃ ࡏࠊ
121✀㢮 ࡢ⤌ ᡂ࡛ ྜᡂࡋ ࡓ ࠋ ࢜ ࣜ ࢦ ࣐࣮ ࢧࣥࣉ ࣝ ࡣ⢊ ○ ࡋ ࡚ NMRᐇ㦂 ࡟ ౑⏝ ࡋࡓ ࠋ㸬 ᫬ 㛫 㡿 ᇦ NMRศศᯒ2.2㸬
40 mg ࢆ┤ᚄ 10 mm ࡢࢳ࣮ࣗࣈ࡟ධࢀࠊࢳ࣮ࣗࣈෆࢆ N2 ࡛⨨᥮ࡋࡓᚋࠊMSEࠊMAPEࠊDQ ࢆᐃࡋࡓࠋ ࢜ࣜࢦ࣐࣮ࡢỈ୙ືᛶࢆホ౯ࡍࡿࡓࡵ࡟ࠊ࢜ࣜࢦ࣐࣮ᮦᩱࢆᾏỈ࡟ᾐࡋࡓࠋ ᾏỈ࡟1᪥ᾐࡋࡓᚋࠊCPMGࢆ ᐃࡋࡓࠋ2.3 ࢤࣝᾐ㏱ࢡ࣐ࣟࢺࢢࣛࣇ࢕࣮ศᯒ
ࢧࣥࣉࣝࡢศᏊ㔞ࡣࠊShodex GPC K-805L ࣒࢝ࣛࢆഛ࠼ࡓ HLC-8420GPC (ᮾࢯ࣮ࠊᮾிࠊ᪥ᮏ)⿦⨨ࢆ౑⏝ࡋࡓࢤࣝ㏱㐣ࢡ࣐ࣟࢺࢢࣛࣇ࢕࣮ (GPC) ศᯒ࡟ࡼࡗ࡚Ỵᐃࡋࡓࠋ ࢡ࣒ࣟࣟ࣍ࣝࢆ⁐㞳ᾮ࡜ࡋ࡚౑⏝ࡋࠊࢧࣥࣉࣝ⃰ᗘࡣ 5 mg/mL ࡜ࡋࡓࠋᐃ᫬ࡢ࣒࢝ࣛ ᗘࡣ40 Υࠊࢧࣥࣉࣝὀ

ධ㔞ࡣ100 ȝLࠊὶ㏿ࡣ1.0 mL/min࡛⾜ࡗࡓࠋ ᳨㔞⥺࡟ࡣ࣏ࣜࢫࢳࣞࣥᶆ‽ࢆ౑⏝ࡋࡓࠋ
2.4 㧗Ỉ୙ືᛶ࢜ࣜࢦ࣐࣮ࡢ㔜せᅉᏊ᥈⣴࠾ࡼࡧ⤌ᡂࡢ᭱㐺໬
T2⦆࿴᭤⥺ࡢỈ୙ືᣦᩘ࡜࢜ࣜࢦ࣐࣮ᵓ㐀࡜ࡢ㛵ಀࡣࠊRFࠊGTMRࢆ౑⏝ࡋ࡚ศᯒࡋࡓࠋ ࢜ࣜࢦ࣐࣮ࡢศᏊᵓ㐀ࡢグ㏙ᏊࡣࠊRDKit ࢆ౑⏝ࡋ࡚⏕ᡂࡋࡓࠋ T2 ⦆࿴᭤⥺ࡢỈ୙ືᛶᣦᩘࢆ㧗࠸ೃ⿵ࡢ࢜ࣜࢦ࣐࣮⤌ᡂࢆண ࡍࡿࡓࡵ࡟ࠊBOࢆ⏝࠸ࡓࠋ－ 217 －

3.1㸬㸬⤖ᯝ࣭⪃ᐹ
3.1㸬
㸬T2⦆࿴᭤⥺ࡢศ㞳
TD-NMR ࢆ౑⏝ࡋࡓ T2⦆࿴᭤⥺ࢆྲྀᚓࡋࡓࠋTD-NMR ࡟ࡼࡗ࡚ᚓࡽࢀࡓ T2⦆࿴᭤⥺ࢆศ㞳ࡍࡿࡇ࡜࡟ࡼࡾࠊ࢜ࣜࢦ࣐࣮ᮦᩱࡢ⤖ྜỈ࡜⮬⏤Ỉࡢ๭ྜࢆィ⟬ࡍࡿࡇ࡜ࡀ࡛ࡁࡓ(Fig.2)ࠋⰾ㤶᪘ࢪ࢝ࣝ࣎ࣥ㓟ࣔࣀ࣐࣮ࢆྵࡴ࢜ࣜࢦ࣐࣮ࡣࠊ௚ࡢࢪ࢝ࣝ࣎ࣥ㓟ࣔࣀ࣐࣮ࢆྵࡴ࢜ࣜࢦ࣐࣮࡜ẚ㍑ࡋ࡚◳㉁ᡂศࡀከ࠿ࡗࡓ (Fig.2a)ࠋ ࢥࣁࢡ㓟࡜࢔ࢪࣆࣥ㓟ࢆྵࡴࢱ࣮࣏࣐࣮ࣜࡣࠊ௚ࡢ࢜ࣜ
ࢦ࣐࣮ࢆྵࡴ࢜ࣜࢦ࣐࣮ࡼࡾࡶ◳࠸ᡂศࡀᑡ࡞࠿ࡗࡓࠋ ⰾ㤶᪘ࢪ࢝ࣝ࣎ࣥ㓟࡜࢔ࢪࣆࣥ㓟ࢆྵࡴࢱ࣮࣏࣐࣮ࣜࡣࠊⰾ㤶᪘ࢪ࢝ࣝ࣎ࣥ㓟ࢆྵࡴ࢜ࣜࢦ࣐࣮࡜ẚ㍑ࡋ࡚ࠊỈ⤖ྜᡂศࡀከ࠿ࡗࡓ
(Fig.2b)ࠋ

Fig. 2. Calculation of the ratio of hard and water bound phases of oligomers.
The fraction of hard phase (a) and water bound phase (b) of oligomers was calculated.
3.2㸬㸬ࣛࣥࢲ࣒ࣇ࢛ࣞࢫࢺ࡟ࡼࡿ㧗Ỉ୙ືᛶ࢜ࣜࢦ࣐࣮ࡢ㔜せᅉᏊ᥈⣴Fig. 3. Exploring important factors of highly water-immobile oligomers by random forest.
Using random forest, we calculated the importance of oligomer composition, terminal ratio, molecularweight (a), and T2 relaxation curve of MSE (b) with water immobility as the objective variable.

－ 218 －

࢜ࣜࢦ࣐࣮ࡢỈ୙ືᛶ࡟࡜ࡗ࡚㔜せ࡞せᅉࢆㄪ࡭ࡿࡓࡵ࡟ࠊࣛࣥࢲ࣒ ࣇ࢛ࣞࢫࢺ࡟ࡼࡾኚᩘࡢ㔜せᗘࢆィ⟬ࡋࡲࡋࡓ (Fig.3)ࠋ Ỉ୙ືᛶ࡜ࡋ࡚CPMGࡢ➨୍ᡂศࡢ๭ྜࢆ┠ⓗኚᩘ࡜ࡋࡓࠋ ศᏊ㔞ࠊ୺㙐࡟ᑐࡍࡿᮎ➃ࡢẚ⋡ࠊ࠾ࡼࡧ࢜ࣜࢦ࣐࣮⤌ᡂࢹ࣮ࢱ࡟࠾ࡅࡿỈ⤖ྜᡂศࡢẚ⋡ࡢ㔜せᛶࡣࠊ୺㙐࡟ᑐࡍࡿᮎ➃ࡢẚ⋡࡛᭱ࡶ㧗ࡃࠊ⥆࠸࡚ศᏊ㔞ࠊࢥࣁࢡ㓟ࠊࢥࣁࢡ㓟ࡀ㧗࠸್࡛࠶ࡗࡓ
(Fig.3a)ࠋ MSE ࢹ࣮ࢱ࡟࠾ࡅࡿỈ⤖ྜᡂศࡢ๭ྜࡢ㔜せᛶࡣࠊ㑄⛣᭤⥺ࡢ๓༙ࡀ㧗࠿ࡗࡓ (Fig.3b)ࠋ
3.3㸬
㸬Generative topographic mapping regression࡟࡟ࡼࡿ㧗Ỉ୙ືᛶ࢜ࣜࢦ࣐࣮ࡢ㔜せᅉᏊ᥈⣴GTMR ࢆᐇ⾜ࡋ࡚ࠊ┠ⓗࡢỈ୙ືᛶࢆᣢࡘ࢜ࣜࢦ࣐࣮ࢆ᳨⣴ࡋࡲࡋࡓ (Fig.4)ࠋ Ỉ୙ືᛶࡢᣦᶆ࡜ࡋ࡚ࠊCPMG ࡢ➨ 1 ᡂศࡢ๭ྜࢆࢱ࣮ࢤࢵࢺኚᩘ࡜ࡋ࡚౑⏝ࡋࡲࡋࡓࠋࢹ࣮ࢱ✵㛫ࡢ୰࡛ࠊỈ⤖ྜᡂศ50%࡛࠶ࡾࠊࢸࣞࣇࢱࣝ㓟ࢆ50%ྵࡴ࢜ࣜࢦ࣐࣮ࡢᗙᶆࢆ⟬ฟࡋ(Fig.4a)ࠊࡑࡢT2⦆࿴᭤⥺(Fig.4b)࡜ࠊRDKitࡢศᏊグ㏙Ꮚ(ᅗ 4c)ࠊ࢜ࣜࢦ࣐࣮ࡢ⤌ᡂࡢೃ⿵(ᅗ 4d)ࢆண

࡛ࡁࡓࠋ

Fig. 4. Exploring important factor of highly water-immobile oligomers by generative topographic
mapping regression.
Using GTMR, we mapped the data space (a), predicted T2 relaxation curves (b), molecular descriptors of
RDKit (c), and oligomer composition (d) using water immobility and composition as objective variables.

3.4㸬㸬࣋࢖ࢬ᭱㐺໬࡟ࡼࡿ㧗Ỉ୙ືᛶ࢜ࣜࢦ࣐࣮ࡢ⤌ᡂண㧗࠸Ỉ୙ືᛶࢆᣢࡘ࢜ࣜࢦ࣐࣮ࡢ⤌ᡂࢆ᭱㐺໬ࡍ
Bayesian Optimization0ᡂࢆ౑⏝ࡋ࡚࣋࢖ࢬ᭱㐺໬ࢆᐇ⾜ࡋࡓ (Fig.5)ࠋ
log(Probabilities of cpmga1)

Ỉ୙ືᛶࡢᣦᶆ࡜ࡋ࡚ࠊCPMG ࡢ➨ 1 ᡂศࡢ๭ྜࢆࢱ࣮ࢤࢵࢺኚᩘ࡜ࡋ࡚౑⏝ࡋࡓࠋ㧗࠸Ỉ୙ືᛶࡀᮇᚅࡉࢀࡓࢧࣥࣉࣝ㸦O001, O092, O108, O025,
O095㸧ࡣࠊCPMGࡢᐇ ್࡟࠾࠸࡚ࡶ⤖ྜỈࡢ๭ྜࡣ㧗࠸್࡛࠶ࡗࡓࠋ
5㸬
㸬References

1071-1081. [3] D. Besghini, et al., Appl Sci, 9 (2019)1801. [4] Y. Date, et al., BMC Chem, 15 (2021) 13. [5]
A. Takamura, et al, Sci. Rep., 11 (2021). [6] S.
Yamada, et al., Int. J. Mol. Sci., 22 (2021) 1086. [7] R.
Yamawaki, et al., Appl. Sci., 11 (2021) 2820.㻌

MeasurementValue

-4

80
70

-6

60

-8

50

-10
40

-12

30

-14
-16

20

-18

10

-20

[1]㻌J. Kikuchi, S. Yamada, Rsc Adv., 11 (2021) 3042630447. [2] P. Nicolella, et al., Soft Matter, 18 (2022)

90
log(Probabilities of cpmga1)-2

Measurement valueࡿࡓࡵ࡟ࠊࢩ࣑࣮ࣗࣞࢺࡉࢀࡓೃ⿵࢜ࣜࢦ࣐࣮⤌0
O001 O092 O108 O025 O095 O099 O076 O031

Fig. 5. Optimization of highly waterimmobile oligomer composition by Bayesian
optimization.
The higher the expected value, the higher themeasured value.

－ 219 －

P37

་⸆ရࡢཎᩱ⢊ᮎ࡟࠾ࡅࡿ⤖ᬗᙧࡢᐃ㔞ホ౯ࢆ┠ⓗ࡜ࡋࡓT2⦆࿴࡟ᑐࡍࡿ㒊ศⓗ᭱ᑠ஧஌ᅇᖐࡢ㐺⏝‫ۑ‬ᒸ⏣ᗣኴ㑻1㸪༓ⴥᝆ▮1㸪ᯘ ⚈ᘯ2㸪⇃⏣ಇ࿃2㸪኱㈏⩏๎11ᐩᒣ኱Ꮫ ⸆Ꮫ㒊 〇๣タィᏛㅮᗙ2᪥་ᕤᰴᘧ఍♫Applying partial least squares regression to T2 relaxation curves for predicting the
crystalline form content of active pharmaceutical ingredient in physical mixtures‫ۑ‬Kotaro Okada1, Yuya Chiba1, Yoshihiro Hayashi2, Shungo Kumada2, Yoshinori Onuki1
1

Laboratory of Pharmaceutical Technology, School of Pharmacy and Pharmaceutical Sciences, Universityof Toyama
2

Nichi-Iko Pharmaceutical Co., Ltd.
This study applied partial least squares (PLS) regression to nuclear magnetic resonance (NMR) relaxation

curves to quantify the free base of an active pharmaceutical ingredient powder. We measured the T2 relaxationof intact and moisture-absorbed physical mixtures of tetracaine free base (TC) and its hydrochloride salt
7&Â+&O 7KHREWDLQHGT2 relaxation curves were analyzed by PLS regression. The entire measured wholeof the T2 relaxation curves was used as input variables and analyzed by PLS regression to quantify the content
of TC in the moisture-DEVRUEHG7&7&Â+&O% DVHGRQVFDWWHUSORWVRIWKHRUHWLFDOYHUVXVSUHGLFWHG7&WKH
obtained PLS model exhibited acceptable coefficients of determination and relatively low root mean squared
error values for calibration and validation data. The statistical values confirmed that an accurate and reliable
PLS model was created to quantify TC in even moisture-DEVRUEHG 7&7&Â+&O 7KH EHQFK-top low-field
NMR instrument used to apply PLS regression to the T2 relaxation curve may be a promising tool in process
analytical technology.
࠙⫼ᬒࠚ་⸆ရ࡟࠾ࡅࡿ᭷ຠᡂศࡢ⤖ᬗᙧࡣࠊ᭷ຠᛶ࠾ࡼࡧᏳ඲ᛶ࡟ᙳ㡪ࢆ୚࠼ࡿࡓࡵࠊ㔜せ࡞ホ౯㡯┠࡛࠶ࡿࠋᙜ◊✲ᐊ࡛ࡣࠊ᫬㛫㡿ᇦNMRἲࢆ฼⏝ࡋࡓࠊᅛᙧΰྜ≀࡟࠾ࡅࡿ⤖ᬗᙧࡢᐃ㔞ホ౯ࢆ㐍ࡵ࡚ࡁࡓࠋ୍㐃ࡢ◊✲࠿ࡽࠊࢯࣜࢵࢻ࢚ࢥ࣮ἲ࡟ࡼࡾ ᐃࡉࢀࡓT2⦆࿴᫬㛫ࡣࠊྵࡲࢀࡿ᭷ຠᡂศࡢ⤖ᬗᛶࢆᐃ㔞ⓗ࡟ホ౯࡛ࡁࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋ࡚ࡁࡓ1,2ࠋࡋ࠿ࡋࠊT2⦆࿴᫬㛫ࡢ⟬ฟ㐣⛬࡟࠾࠸࡚ࠊࣇ࢕ࢵࢸ࢕ࣥࢢゎᯒ࡟⏝࠸ࡿ⌮ㄽᘧ࡛ࡣࠊ㡯ᩘࡸ࢜ࣇࢭࢵࢺ㡯ࡢ㑅ᢥ࡟⤒㦂ⓗ࡞ุ᩿ࢆせࡍࡿࠋ࠙┠ⓗࠚᮏ◊✲࡛ࡣࠊT2⦆࿴ࡢ᭤⥺ࢆ⏝࠸࡚ࠊపศᏊ㔞ࡢ᭷ຠᡂศ࡟࠾ࡅࡿ⤖ᬗᙧࡢᐃ㔞ホ౯ࢆ⾜࠺ࡇ࡜ࢆ┠ⓗ࡜ࡋࠊࢣ࣓ࣔࢺࣜࢵࢡࢫࡢ୍✀࡛࠶ࡿ㒊ศⓗ᭱ᑠ஧஌㸦partial leastsquares㸹PLS㸧ᅇᖐࢆT2⦆࿴ࡢゎᯒ࡟㐺⏝ࡋࡓࠋࡉࡽ࡟ࠊ྾
‵ࡋࡓỈࡀᮏᡭἲ࡟ཬࡰࡍᙳ㡪ࢆホ౯ࡍࡿࡓࡵࠊ྾‵ࡋࡓΰ

Fig. 1. Chemical structure ofྜ≀ࢆㄪ〇ࡋࠊྠᵝࡢゎᯒࢆ⾜ࡗࡓࠋ࡞࠾ࠊPLSᅇᖐ࡛ࡣࠊ

tetracaine free base (TC).

T2⦆࿴ࡢ᭤⥺ࢆᵓᡂࡍࡿ ᐃⅬࢆࠊㄝ᫂ኚᩘ࡜ࡋ࡚ᢅࡗࡓࠋ
T2⦆࿴㸪་⸆ရ㸪ࢣ࣓ࣔࢺࣜࢵࢡࢫ
‫࠺ࢁࡓ࠺ࡇࡔ࠿࠾ۑ‬㸪ࡕࡤࡺ࠺ࡸ㸪ࡣࡸࡋࡼࡋࡦࢁ㸪ࡃࡲࡔࡋࡹࢇࡈ㸪࠾࠾ࡠࡁࡼࡋࡢࡾ

－ 220 －

࠙᪉ἲࠚᕷ㈍ࡢࢸࢺࣛ࢝࢖ࣥࣇ࣮ࣜయ㸦TC㸧ࠊࢸࢺࣛ࢝࢖ࣥሷ㓟ሷ㸦TCÂHCl㸧ࢆ㉁㔞ẚ20%้
ࡳ࡛ΰྜࡋࠊ≀⌮ΰྜ≀࡜ࡋࡓࠋࡲࡓࠊ≀⌮ΰྜ≀ࢆ25Υ94%RH࡟࡚ಖᏑࡋࠊ྾‵ࡋࡓ≀⌮ΰྜ≀࡜ࡋࡓࠋㄪ〇ࡋࡓྛ≀⌮ΰྜ≀ࡢT2⦆࿴ࡣࠊప☢ሙNMR⿦⨨㸦minispec mq20ࠊ% ruker㸧࡟ࡼࡾࢯࣜࢵࢻ࢚ࢥ࣮ἲࢆ⏝࠸࡚ࠊࡑࢀࡒࢀࠊ5ᅇ ᐃࡋࡓࠋ
PLSᅇᖐࡣJMP® Pro 16㸦SAS institute㸧ࢆ⏝࠸࡚⾜ࡗࡓࠋㄝ᫂ኚᩘࢆT2⦆࿴ࡢ᭤⥺ࢆᵓᡂࡍࡿ
ᐃⅬ࡜ࡋࠊ┠ⓗኚᩘࢆ≀⌮ΰྜ≀࡟ྵࡲࢀࡿࣇ࣮ࣜయࡢ๭ྜ࡜ࡋࡓࠋྲྀᚓࡋࡓ5ࡘࡢT2⦆࿴ࡢ࠺ࡕ4ࡘࢆcalibration setࠊ1ࡘࢆvalidation set࡜ࡋࡓࠋcalibration setࢆ⏝࠸࡚ᅇᖐࣔࢹࣝࢆసᡂࡋࠊ
validation setࢆ⏝࠸࡚ᅇᖐࣔࢹࣝࡢ᳨ドࢆ⾜ࡗࡓࠋࣔࢹࣝ⢭ᗘࡢᣦᶆ࡜ࡋ࡚ࠊvariable importancein projection㸦VIP㸧್ࠊỴᐃಀᩘ㸦R2㸧࠾ࡼࡧ஧஌ᖹᆒᖹ᪉᰿ㄗᕪ㸦RMSE㸧ࢆ⏝࠸ࡓࠋ࠙⤖ᯝ࣭⪃ᐹࠚ᭱ึ࡟ࠊTC㸭TCÂHClࡢ≀⌮ΰྜ≀࡟ࡘ࠸࡚ࠊ ᐃ࣭ゎᯒࢆ⾜ࡗࡓࠋPLSᅇᖐࡢ⤖ᯝࠊvalidation set࡟࠾࠸࡚ࠊR2ࡣ0.998ࠊRMSEࡣ1.587࡛࠶ࡾࠊ≀⌮ΰྜ≀࡟ྵࡲࢀࡿࣇ࣮ࣜయ
ࡢ๭ྜࢆ⢭ᗘⰋࡃண ࡛ࡁࡓࠋḟ࡟ࠊ྾‵ࡀᅇᖐࣔࢹࣝࡢண ⢭ᗘ࡟୚࠼ࡿᙳ㡪ࢆ᳨ドࡍࡿࡓࡵࠊ྾‵ࡋࡓTC㸭TCÂHClࡢ≀⌮ΰྜ≀࡟ࡘ࠸࡚ࠊྠᵝࡢ ᐃ࣭ゎᯒࢆ⾜ࡗࡓ㸦Fig. 2a㸧ࠋPLSᅇᖐࡢ⤖ᯝࠊvalidation set࡟࠾࠸࡚ࠊR2ࡣ0.999ࠊRMSEࡣ1.304࡛࠶ࡾࠊᮍ྾‵ࡢ≀⌮ΰྜ≀࡜ྠᵝ࡟ࠊྵࡲࢀࡿࣇ࣮ࣜయࡢ๭ྜࢆ
ணྍ⬟࡛࠶ࡗࡓ㸦Fig. 2b㸧ࠋ྾‵ࡋࡓ≀⌮ΰྜ≀ࡢሙྜࠊVIP್ࡣT2⦆࿴ᣲືࡢ඲ᇦ࡛㧗࠸್ࢆ♧ࡋ㸦> 0.8㸧ࠊ≉࡟0–0.03 msࡢ㡿ᇦ࡛┦ᑐⓗ࡟㧗࠸್ࢆ♧ࡋࡓ㸦Fig. 2c㸧ࠋ0–0.03 msࡣࠊ᭷ຠᡂศ⮬య࡟⏤᮶ࡍࡿ㡿ᇦ࡛࠶ࡾࠊ
సᡂࡉࢀࡓᅇᖐࣔࢹࣝࡣጇᙜ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ୍᪉࡛ࠊ0.03–0.3 msࡣ྾‵ࡋࡓỈ࡟⏤᮶ࡍࡿ㡿ᇦ࡛࠶ࡾࠊࡇࡢ㡿ᇦ࡟࠾࠸࡚ࡶVIP್ࡣ0.8௨ୖ࡜㧗࠸್ࢆ♧ࡋࡓࡇ࡜࠿ࡽࠊᅇᖐࣔࢹࣝࡣ᭷ຠ
ᡂศ࠾ࡼࡧ྾‵ࡋࡓỈࡢ୧᪉࡟ᇶ࡙ࡁసᡂࡉࢀࡓࡇ࡜ࡀุ᫂ࡋࡓࠋ
௨ୖ࠿ࡽࠊࢯࣜࢵࢻ࢚ࢥ࣮ἲ࠿ࡽᚓࡽࢀࡓT2⦆࿴࡟ᑐࡋࠊPLSᅇᖐࢆ㐺⏝ࡍࡿࡇ࡜࡛ࠊ྾‵ࡢ᭷↓ࢆၥࢃࡎࠊ≀⌮ΰྜ≀࡟ྵࡲࢀࡿ᭷ຠᡂศࡢ⤖ᬗᙧࢆᐃ㔞࡛ࡁࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓࠋ

Fig. 2. (a) T2 relaxation curves of moisture-absorbed physical mixture (PM) of tetracaine (TC) and
WHWUDFDLQHK\GURFKORULGH 7&Â+&O  E VFDWWHUSORWVRIWKHRUHWLFDO7&YHUVXVSUHGLFWHG7&FRQWHQW
by partial least squares 3/6 PRGHO F YDULDEOHLPSRUWDQFHLQSURMHFWLon (VIP) values of input
variables of the PLS models to determine TC content. Input variables correspond to theacquisition time of T2 relaxation curves.
References(1) Okada et al. (2019) T2 Relaxation Study to Evaluate the Crystalline State of Indomethacin Containing Solid
Dispersions Using Time-Domain NMR. Chem. Pharm. Bull. 67, 580–586.

(2) Okada et al. (2020) Qantitative Evaluation of the Crystallinity of Indomethacin Using 1H T2 Relaxation% HKDYLRUV0HDVXUHGE\7LPH' RPDLQ105J. Pharm. Sci. 109, 2257–2584.

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P38Y

࢚ࢳࣞࣥ࢔࢖࢜ࣀ࣐࣮ࡢᵓ㐀࡜⇕ຎ໬㐣⛬࡟㛵ࡍࡿᅛయNMRἲ࡜ESRἲ࡟ࡼࡿ◊✲‫୕ۑ‬ᙳ᪼ᖹ㸪୰⃝༓㤶Ꮚ㸪ὸ㔝ᩔᚿ
1㜵⾨኱Ꮫᰯ࣭ᛂ⏝໬Ꮫ⛉Structure and degradation process of an ethylene ionomer investigated by solid-state
NMR and ESR‫ۑ‬Shohei Mikage1, Chikako T. Nakazawa1, Atsushi Asano1
1

Department of Applied Chemistry, National Defense Academy
Annealing effect of Na+ cation on structure and degradation of ethylene ionomers was investigated by thehigh-resolution solid-state 13C NMR and ESR. The 13C CPMAS NMR and T1C experiments showed that theregularity of the orthorhombic crystal is improved and that the crystallinity increased after annealing at 65°C.
The temperature-dependent 13C NMR spectra showed that the peak intensity decreases with temperature(beyond 55°C) and disappeared at 86°C, while the orthorhombic crystal remains at the temperature. The 13C
CPMAS NMR spectra after heat-treatment at 200°C showed the appearance of new signals assigned tovarious esters with heating period. The ESR spectra detected that the radicals increase significantly with
degree of neutralization. The expected thermal degradation process was discussed from both peak changesof NMR and ESR.
㸺⥴ゝ㸼࣓ࢱࢡࣜࣝ㓟㸦MAA㸧࡜࢚ࢳࣞࣥ㙐㸦E㸧࠿ࡽ࡞ࡿࣛࣥࢲ࣒ඹ㔜ྜయ㸦EMAA㸧ࡣࠊMAA㒊఩ࡢゎ㞳ࡋࡓ࢝ࣝ࣎࢟ࢩᇶ㸦COOíᇶ㸧࡜㔠ᒓ࢖࢜ࣥࡀ㟼㟁┦஫స⏝࡟ࡼࡾจ㞟ࡍࡿࡇ࡜࡛ࠊ࢖࢜ࣥ
఍ྜయ㸦࢖࢜ࣥࢡࣛࢫࢱ࣮㸧ࢆᙧᡂࡍࡿࠋࡇࡢ࢖࢜ࣥ఍ྜయࡀᙉ࠸ᯫᶫⅬ࡜ࡋ࡚Ꮡᅾࡍࡿࡇ࡜࡛ࠊ
ᙉ㠌ᛶࡸ⪏⾪ᧁᛶ࡞࡝ࡢ≀ᛶࡀྥୖࡍࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿ 1)ࠋEMAAࡸEMAA࢔࢖࢜ࣀ࣐࣮ࡢ
DSC᭤⥺࡟ࡣࠊ65ႏ㏆ഐ࡟⛛ᗎ㸫↓⛛ᗎ㌿⛣࡟ࡼࡿ࡜ࡉࢀࡿ྾⇕ࣆ࣮ࢡࡀほࢀ࡚࠸ࡿࠋࡉࢀࡿࡇ࡜ࡀ▱ࡽ

ᗘྍኚNMRࢫ࣌ࢡࢺࣝࡢゎᯒ࡞࡝࠿ࡽࠊࡇࡢ྾⇕ࣆ࣮ࢡࡢ⏤᮶࡟ࡘ࠸᳨࡚ウࡋࡓࠋ

ࡉࡽ࡟ࠊ200ႏࡢ㧗⇕ฎ⌮࡛㉳ࡇࡿᯫᶫ཯ᛂ࡟ᑐࡍࡿ࢖࢜ࣥ఍ྜయࡢᙳ㡪ࢆᅛయ㧗ศゎ⬟ 13C

CPMAS NMRἲ࡜ESRἲࢆ⏝࠸᳨࡚ウࡋࡓࠋ㸺ᐇ㦂࣭ゎᯒ㸼
EMAA࡜EMAA࢔࢖࢜ࣀ࣐࣮ࡣࠊ୕஭࣭ࢹ࣏࣏ࣗࣥࣜࢣ࣑࢝ࣝ♫ࡼࡾᥦ౪ࡉࢀࡓࠋ࡝ࡕࡽࡶ㉁㔞
ẚ࡛15 wt%ࡢMAA㒊ࢆ᭷ࡋࠊ࢔࢖࢜ࣀ࣐࣮ࡣ࢝ࣝ࣎࢟ࢩᇶࡢx %ࡀNa+࢖࡛࢜ࣥ୰࿴ࡉࢀ࡚࠸ࡿ㸦EMAA- x Na㸧ࠋ⇕ฎ⌮ࡣࢭ࣑ࣛࢵࢡ࣍ࢵࢺࣉ࣮ࣞࢺࢆ⏝࠸࡚✵Ẽ㞺ᅖẼୗ200 ± 5ႏ࡛⾜ࡗࡓᚋࠊᾮయ❅⣲࡛ᛴ෭ࡋ࡚⇕ฎ⌮ࡢ㐍⾜ࢆṆࡵࡓࠋᅛయ㧗ศゎ⬟13C NMR ࢫ࣌ࢡࢺࣝࡣࠊVarian♫〇NMR Systems 400WB ࢆ⏝࠸࡚ ᐃࡋࡓࠋ1H
᰾ࡢ90°ࣃࣝࢫᖜࡣ3.7 ȝsࠊ஺ᕪศᴟ㸦CP㸧ࡢࣛࢪ࢜Ἴᙉᗘࡣ1Hഃࡀ54.3 kHzࠊ13Cഃࡀ55.6 kHzࠊ1Hࢹ࢝ࢵࣉࣜࣥࢢ㸦DD㸧ࡢࣛࢪ࢜Ἴᙉᗘࡣ67.6 kHzࠊMAS ㏿ᗘࡣ6ࡲࡓࡣ7 kHz ࡟タᐃࡋ࡚ᐊ ࡛
ᐃࡋࡓࠋESRࢫ࣌ࢡࢺࣝࡣࠊBRUKER♫〇ࡢ༟ୖᆺ㟁Ꮚࢫࣆࣥඹ㬆⿦⨨㸦EMXnano㸧ࢆ⏝࠸࡚࢚ࢳࣞࣥ࢔࢖࢜ࣀ࣐࣮㸪⦆࿴᫬㛫㸪ࣛࢪ࢝ࣝ‫࠸࡬࠺ࡻࡋࡆ࠿ࡳۑ‬㸪࡞࠿ࡊࢃࡕ࠿ࡇ㸪࠶ࡉࡢ࠶ࡘࡋ

－ 222 －

ᤲᘬ☢ሙ୰ᚰࢆ343.86 ± 0.12 mTࠊᤲᘬ᫬㛫30 sࠊ✚⟬ᅇᩘ256ᅇ࡟タᐃࡋࠊᐊ ࡛ ᐃࡋࡓࠋ♧ᕪ㉮ᰝ⇕㔞 ᐃ㸦DSC㸧ࡣࠊPerkinElmer♫〇DSC 8500ࢆ⏝࠸࡚ ᐃࡋࡓࠋ᪼ 㝆

࡜ࡶ࡟2 ႏ/min࡛

20ႏ࠿ࡽ130ႏࡲ࡛ࡢ⠊ᅖ࡛❅⣲㞺ᅖẼୗ࡛⾜ࡗࡓࠋࣃ࣮ࢪ❅⣲࢞ࢫὶ㔞ࡣ20 ml/min࡛࠶ࡿࠋ㸺⤖ᯝ࣭⪃ᐹ㸼
 Fig. 1࡟ࠊEMAA࡜EMAA-54NaࡢDSC ᐃࡢ⤖ᯝࢆ♧ࡍࠋ⇕ฎ⌮๓࡛ࡣࠊ60°C㏆ഐ࡟ᑠࡉ࡞྾⇕ࣆ࣮ࢡ㸦Ti㸧࡜90°C௜㏆࡟CH2㙐ࡢ⤖ᬗ┦ࡢ⼥ゎ࡟㉳ᅉࡍࡿ྾⇕ࣆ࣮ࢡ㸦Tm㸧ࡢ㸰ࡘࡢࣆ࣮ࢡࡀほࡉࢀࡿ㸦㯮⥺㸧ࠋTiࡼࡾࡶࢃࡎ࠿࡟㧗࠸65°C࡛60ศ㛫࢔ࢽ࣮ࣜࣥࢢࡋࡓᚋ࡟DSC ᐃࡍࡿ࡜㸦㉥⥺㸧ࠊEMAA࡜EMAA-54Na࡜ࡶ࡟Tiࣆ࣮ࢡࡀ70°C௜㏆ࡲ࡛ࢩࣇࢺࡍࡿࠋࡇࡢࡼ࠺࡞ ᗘᒚṔ࡟ࡼ
ࡿCH2㙐ࡢ⤖ᬗ┦ࡢኚ໬ࢆほ ࡍࡿࡓࡵࠊ ᗘྍኚ13C CPMAS NMRࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓࠋࡇࡇ
࡛ࡣࠊ࢔ࢽ࣮ࣜࣥࢢ๓ᚋࡢEMAA࡜EMAA-54Naࡢᅛయ㧗ศゎ⬟13C CPMAS NMRࢫ࣌ࢡࢺࣝࢆFig.
2࡟♧ࡍࠋ࢔ࢽ࣮ࣜࣥࢢ๓ࡢࢫ࣌ࢡࢺࣝ࡟ὀ┠ࡍࡿ࡜ࠊ33 ppm௜㏆࡟⤖ᬗ┦⏤᮶ࡢCH2ࣆ࣮ࢡࠊ31
ppm௜㏆࡟㠀ᬗ┦⏤᮶ࡢCH2ࣆ࣮ࢡࡀほ ࡉࢀࡓࠋ⤖ᬗ┦⏤᮶ࡢCH2ࣆ࣮ࢡࡣࠊT1Cࡢ ᐃ㏵୰࡟࠾
ࡅࡿῶ⾶ഴྥ࠿ࡽࠊ㸱ࡘࡢᡂศ࡛ᵓᡂࡉࢀ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡓࠋ33.9 ppmࡢࣆ࣮ࢡࡣ༢ᩳᬗ
㸦Monoclinic㸧ࠊ33.4 ppmࡢࣆ࣮ࢡࡣCOOHᇶ࠶ࡿ࠸ࡣ࢖࢜ࣥ఍ྜయ㏆ഐ࡟఩⨨ࡍࡿCH2ᇶࠊ32.8
ppmࡢࣆ࣮ࢡࡣᩳ᪉ᬗ㸦Orthorhombic㸧࡟ᖐᒓࡉࢀࡿ࡜⪃࠼ࡽࢀࡓࠋ࢔ࢽ࣮ࣜࣥࢢᚋࡢࢫ࣌ࢡࢺࣝ
࡛ࡣࠊᩳ᪉ᬗࣆ࣮ࢡࡀ㢧ⴭ࡟ቑຍࡋࡓࠋࡲࡓࠊ ᗘྍኚNMRࢫ࣌ࢡࢺࣝ࠿ࡽࡣࠊ༢ᩳᬗࡀ70°C௜
㏆࡛㢧ⴭ࡟ῶᑡࡋࠊࡑࡢᚋᾘኻࡋࡓࠋࡍ࡞ࢃࡕࠊTiࡢ୍ᅉࡣ༢ᩳᬗࡢ⼥ゎ࡟࠶ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
ࡉࡽ࡟ࠊ࢔ࢽ࣮ࣜࣥࢢ๓ᚋ࡛ࡢT1C್ࡢኚ໬ࢆẚ㍑ࡋ࡚ࡳࡿ࡜ࠊ༢ᩳᬗ࡛ࡣ࡯࡜ࢇ࡝ኚ໬ࡀ࡞࠸ࡢ
࡟ᑐࡋࠊᩳ᪉ᬗ࡛ࡣT1C್ࡢ㛗࠸ᡂศࡀEMAA࡛8.7s0.7 s࠿ࡽ24s2 sࠊEMAA-54Na࡛6.4s0.8 s࠿ࡽ21s2 s࡜㛗ࡃ࡞ࡗ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ⇕ฎ⌮ᚋ࡟ᩳ᪉ᬗࡀቑຍࡋࡓࡇ࡜ࠊT1Cࡀ኱ᖜ࡟㛗ࡃ࡞ࡗࡓࡇ࡜࠿ࡽࠊTiࡢ྾⇕ࣆ࣮ࢡࡣ༢ᩳᬗࡢ⼥ゎ࡜ඹ࡟࢚ࢳࣞࣥ㙐ࡢ⛛ᗎ㸫↓⛛ᗎ㌿⛣ࡀཎᅉ࡜࡞ࡗ࡚ฟ⌧ࡋ࡚࠸ࡿ࡜ゝ࠼ࡓࠋ ḟ࡟ࠊ200ႏ࡛⇕ฎ⌮ࡋࡓ࡜ࡁࡢᯫᶫ཯ᛂ࡟࠾ࡅࡿ࢖࢜ࣥ఍ྜయࡢᙳ㡪࡟ࡘ࠸࡚ㄪ࡭ࡓࠋFig. 3
࡟EMAA࠾ࡼࡧEMAA-54Naࡢᅛయ㧗ศゎ⬟13C CPMAS NMRࢫ࣌ࢡࢺࣝ࡟ࡘ࠸࡚ࠊ࢝ࣝ࣎ࢽࣝ㡿ᇦࢆᣑ኱ࡋ࡚♧ࡋࡓࠋ⇕ฎ⌮๓ࡣ185 ppm㏆ഐ࡟MAA㒊఩ࡢCOOHᇶ࡟ᖐᒓࡉࢀࡿࣆ࣮ࢡࡀほFig. 1. Observed DSC spectra ofFig. 2. Observed and expanded solid-state 13C CPMASEMAA and EMAA54-Na before and

NMR spectra for CH2 region of EMAA and EMAA-54Na

after annealing.

before and after annealing.

－ 223 －

Fig. 3. Observed and simulated 13C CPMAS NMR spectra expanded in the carbonyl region of (A) EMAA
and (B) EMAA-54Na before and after heat treatment.
ࡉࢀࡿࠋEMAA-54Na࡛ࡣࠊࡇࡢࣆ࣮ࢡ࡟ຍ࠼࡚ࠊ188 ppm࡟Na+࡜┦஫స⏝ࡋ࡚࠸ࡿCOOHᇶ㸦COOí
Na+ᇶ㸧ࣆ࣮ࢡࠊ183 ppm࡟ゎ㞳ࡋࡓCOOHᇶ㸦COOíᇶ㸧ࣆ࣮ࢡࡀほࡉࢀࡓࠋ⇕ฎ⌮ᚋ࡟ࡣ210

ppm௜㏆࠾ࡼࡧ170 ppm௜㏆ࢆ୰ᚰ࡟᪂ࡓ࡞ࣆ࣮ࢡࡀほ ࡉࢀࡓࠋ᪤ሗࡢ⇕ฎ⌮࣏࢚ࣜࢳࣞࣥࡢ13C
NMRࢫ࣌ࢡࢺࣝ࡜ࡢẚ㍑࠿ࡽࠊ220㹼190 ppm௜㏆ࡢࣆ࣮ࢡࡀࢣࢺࣥ࡜࢔ࣝࢹࣄࢻࠊ180㹼165 ppm
௜㏆ࡢࣆ࣮ࢡࡀ㓟࡜࢚ࢫࢸࣝ㢮࡛࠶ࡿ࡜ᖐᒓࡉࢀࡓ2)ࠋ࢚ࢫࢸࣝࡢⓎ⏕㔞ࡣ⇕ฎ⌮᫬㛫࡟కࡗ࡚ቑ
኱ࡋࠊEMAA-54NaࡼࡾࡶEMAAࡢ᪉ࡀከ࠸ࡇ࡜ࡀࢃ࠿ࡗࡓࠋ୍᪉࡛ࠊEMAA࡛ࡣ185 ppmࡢCOOH
ᇶࣆ࣮ࢡ㸦ᶳⰍ㸧ࠊEMAA-54Na࡛ࡣ188 ppmࡢCOOí Na+ᇶࣆ࣮ࢡ㸦⣸Ⰽ㸧ࡀ⇕ฎ⌮࡟క࠸㢧ⴭ࡟ῶᑡࡋࡓࠋࡇࢀࡣࠊEMAA࠾ࡼࡧEMAA-Naࡢ࣓ࢱࢡࣜࣝ㓟㒊఩࡛ࠊ⇕ฎ⌮࡟ࡼࡾࣛࢪ࢝ࣝࡀⓎ⏕ࡋࠊᯫᶫ཯ᛂࡀ㐍⾜ࡋ࡚࢚ࢫࢸࣝᇶ࡞࡝࡟ኚ໬ࡋࡓࡓࡵ࡛࠶ࡿࠋḟ࡟ࠊ⇕ฎ⌮࡟కࡗ࡚㉳ࡇࡿࣛࢪ࢝ࣝ⏕ᡂࡸࠊࡑࡢࣛࢪ࢝ࣝ✀ࢆࡼࡾᐃ㔞ⓗ࡟ゎᯒࡋࡓࠋ Fig. 4࡟⇕ฎ⌮᫬㛫480ศࠊ1080ศ࠾ࡼ
ࡧ3000ศࡢ᫬ࡢEMAA࠾ࡼࡧEMAA࢔࢖
࢜ࣀ࣐࣮ࡢESRࢫ࣌ࢡࢺࣝࢆ♧ࡍࠋほࡉࢀࡓࣆ࣮ࢡࡣ୍ぢࢩࣥࢢࣞࢵࢺࣆ࣮ࢡ
࡛࠶ࡾࠊ⇕ฎ⌮᫬㛫ࡢቑຍ࡟కࡗ࡚ࣆ࣮
ࢡᙉᗘࡀቑ኱ࡋࡓࠋࡇࡢࣆ࣮ࢡᙉᗘࡣࠊ
Na+࢖࢜ࣥ࡟ࡼࡿ୰࿴ᗘࡀ㧗࠸࡯࡝ᙉࡃ
ほࡉࢀࡓࠋࡇࢀࡣNMR࠿ࡽほ ࡉࢀࡓ࢚ࢫࢸࣝࣆ࣮ࢡࡢቑຍഴྥ࡜ࡣ㏫ࡢ㛵ಀ࡛࠶ࡿࠋࡍ࡞ࢃࡕࠊほ ࡉࢀࡓࣛࢪ࢝ࣝ
㔞ࡣࠊ࢚ࢫࢸࣝᇶ࡞࡝࡬ࡢᯫᶫ཯ᛂ࡟㛵୚ࡋ࡚࠸࡞࠸࠿ࠊ࠶ࡿ࠸ࡣ㛵୚ࡋࡓᚋ࡟
ṧᏑࡋࡓࣛࢪ࡛࢝ࣝ࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ

Fig. 4. ESR spectra of EMAA, EMAA-30Na, and EMAA54Na heated at 200ႏ.

⇕ฎ⌮୰ࡢ཯ᛂࢆࡼࡾヲ⣽࡟⪃ᐹࡍࡿࡓࡵ࡟ࠊ⇕ฎ⌮᫬㛫ࡢቑຍ࡟క࠺ࣛࢪ࢝ࣝ㔞ࡢኚ໬࡟╔┠ࡋࡓࠋFig. 5࡟ࡣࠊEMAA㸦㯮ᐇ⥺࡜‫ڦ‬㸧࠾ࡼࡧEMAA-54Na㸦㟷ᐇ⥺࡜Ÿ㸧ࡢࣛࢪ࢝ࣝ㔞㸦ࢫࣆࣥ㔞㸧ࢆ⇕ฎ⌮᫬㛫࡟ᑐࡋ࡚ࣉࣟࢵࢺࡋࡓࠋࣛࢪ࢝ࣝࡣ⇕ฎ⌮᫬㛫࡜ඹ࡟ቑຍࡋࠊEMAA࡛ࡣ2000
ศࠊEMAA-54Na࡛ࡣ1300ศ௜㏆ࢆቃ࡟஧ẁ㝵࡛ቑຍࡋࡓࠋࡲࡓࠊ⇕ฎ⌮ᙜึࡣ2.005௜㏆࡛࠶ࡗࡓ
g್ࡀࠊ⇕ฎ⌮࡟క࠸2.003௜㏆ࡲ࡛పୗࡋࡓࠋ࢝ࣝ࣎ࢽࣝࣛࢪ࢝ࣝ㸦COO࣭㸧ࡢg್ࡣ2.005ࠊ࢔ࣝࢥ࢟ࢩࣛࢪ࢝ࣝ㸦CO࣭㸧ࡣ2.004ࠊⅣ⣲ࣛࢪ࢝ࣝ㸦C࣭㸧ࡣ2.003࡟┦ᙜࡍࡿࡇ࡜࠿ࡽࠊᑡ࡞ࡃ࡜ࡶ

－ 224 －

Fig. 5. Spin quantity obtained from peak fitting against the heating period for EMAA (A) and EMAA54Na (A).
㸱✀㢮ࡢࣛࢪ࢝ࣝⓎ⏕ࡀ♧၀ࡉࢀࡿࠋࡑࡇ࡛ࠊᐇ ࡢESRࢫ࣌ࢡࢺࣝࡀࠊࡇࡢ㸱✀㢮ࡢ࠸ࡎࢀ࠿ࡢ
ࣛࢪ࢝ࣝ࡟ࡼࡿ࡜௬ᐃࡋ࡚ࢩ࣑࣮ࣗࣞࢩࣙࣥࡋࡓࠋEMAA࡛ࡣࠊCOO࣭ࣛࢪ࢝ࣝ㸦ᶳⰍ㸧࡜C࣭ࣛ
ࢪ࢝ࣝ㸦⥳Ⰽ㸧ࡢ㸰✀㢮ࡢࣛࢪ࢝ࣝⓎ⏕ࢆ௬ᐃࡍࡿ࡜࠺ࡲࡃ෌⌧࡛ࡁࡓࠋฎ⌮᫬㛫2000ศ௜㏆ࡲ
࡛ࡣࠊC࣭ࣛࢪ࢝ࣝࡢࢫࣆࣥ㔞ࡀ㢧ⴭ࡟ቑຍࡋࠊ2000ศ௨㝆࡛ࡣ೵⁫ࡋࡓࠋ୍᪉࡛ࠊCOO࣭ࣛࢪ࢝ࣝࡣ⦆ࡸ࠿࡟ቑຍࡋ⥆ࡅࡓࠋEMAA-54Na࡛ࡣࠊ㸱✀㢮ࡢࣛࢪ࢝ࣝࢆ௬ᐃࡍࡿ࡜࠺ࡲࡃ෌⌧࡛ࡁࡓࠋ⇕ฎ⌮᫬㛫1300ศ௜㏆ࡲ࡛ࡣࠊCO࣭ࣛࢪ࢝ࣝ㸦⣸Ⰽ㸧ࠊCOO࣭ࣛࢪ࢝ࣝ㸦ᶳⰍ㸧ࠊC࣭ࣛࢪ࢝ࣝ
㸦⥳Ⰽ㸧ࡢ㡰࡟ࢫࣆࣥ㔞ࡀቑຍࡋࡓࡀࠊ1300ศ௨㝆࡛ࡣCOO࣭ࣛࢪ࢝ࣝࡢࢫࣆࣥ㔞ቑຍࡣ೵⁫ࡋࠊ
C࣭ࣛࢪ࢝ࣝ࡜CO࣭ࣛࢪ࢝ࣝࡀቑຍࡋࡓࠋ௨ୖࡢNMR࡜ESRࡢ⤖ᯝ࠿ࡽࠊண᝿ࡉࢀ
ࡿࣛࢪ࢝ࣝ⏕ᡂ཯ᛂࢆ᳨ウࡋࡓ㸦Fig.6㸧ࠋ
EMAA࡛ࡣࠊ⇕ฎ⌮᫬㛫ࡢ2000ศࡲ࡛ࡣࠊ
COOHᇶࡀ⬺㞳ࡋࡓࡾ㸦ձ㸧ࠊH࣭ࡢゎ㞳ࡸ㸦ղ㸧ࡉࡽ࡟㓟໬཯ᛂࡀ㐍ࢇ࡛CO2ࡀ⬺㞳ࡍࡿࡇ࡜࡛㸦ճ㸧ࠊC࣭ࣛࢪ࢝ࣝ࡜COO࣭ࣛࢪ࢝ࣝࡀ⏕ᡂࡍࡿࠋ2000ศ௨㝆࡛ࡣCOO࣭ࣛࢪ࢝ࣝࡢࡳࡀቑຍࡋ⥆ࡅࡓࡇ࡜࠿ࡽࠊH࣭ࡢゎ㞳㸦ղ㸧ࡢࡳࡀ⥅⥆ࡋࡓ࡜⪃࠼ࡽࢀࡿࠋ
ࡇࢀ࡟ᑐࡋࠊEMAA-54Na࡛ࡣࠊ⇕ฎ⌮᫬㛫
ࡢ1300ศࡲ࡛ࡣࠊCOOí Na+ᇶ࠿ࡽONaᇶࡀ⬺㞳ࡋࡓࡾ㸦ձ̓㸧ࠊONaᇶࡀ⤖ྜࡋࡓࡾࡍ
ࡿࡇ࡜࡛㸦ղ̓㸧ࠊCOO࣭ࣛࢪ࢝ࣝ࡜CO࣭ࣛࢪ࢝ࣝࡢ⏕ᡂࡀඃໃ࡜࡞ࡗࡓ࡜⪃࠼ࡽࢀ
ࡓࠋ1300ศ௨㝆࡛ࡣࠊ㓟໬཯ᛂࡀࡉࡽ࡟㐍⾜ࡍࡿࡇ࡜࡛CO࡜CO2ࡀ⬺㞳ࡋ
㸦ճ̓㸪
մ̓㸧ࠊ
C࣭ࣛࢪ࢝ࣝࡀ᭱ࡶ㢧ⴭ࡟ቑຍࡋࡓ࡜⪃࠼ࡽࢀࡓࠋ

Fig. 6. Expected radical formation reaction for EMAA(A) and EMAA-54Na (B).

㸺ཧ⪃ᩥ⊩㸼1) ▮㔝⤀୍ࠊᖹἑᰤస┘ಟࠊࠕ࢔࢖࢜ࣀ࣐࣮࣭࢖࢜ࣥᛶ㧗ศᏊᮦᩱࡢ㛤Ⓨࠖࢩ࣮࢚࣒ࢩ࣮ฟ∧ 2009.
2) R.A. Assink, et al., Macromolecules, 33, 4023-4029, (2000).

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P39ࢢ࢔ࢽࣥᅄ㔜㙐࡬ࡢ㝧࢖࢜ࣥ⤖ྜࡢ఩⨨㑅ᢥᛶ࡜஺᥮㐣⛬ࡢ◊✲‫ۑ‬ᑎᮧ⌶ኸ㸪㔠ᢡ㈼஧㸯1ி㒔ᕤⱁ⧄⥔኱Ꮫ኱Ꮫ㝔࣭ᶵ⬟≀㉁໬Ꮫᑓᨷ

Study on selectivity and exchange processes of cations binding to G-quadruplex‫ۑ‬Teramura Takuo1, Kenji Kanaori1
1

Department of Functional Chemistry, Kyoto Institute of Technology
G-quadruplex is a non-canonical structure formed by the folding of G-rich DNA strands. The G-

quadruplex has cation binding sites of Na+ and K+, between the G-quartet planes, and takes different
topologies depending on the cations. In this study, we used 15NH4+ with Na+ or K+ to analyze the selectivity
and affinity of the cations to the binding sites of human telomeric G-quadruplex by chemical exchange
cross peaks in the NOESY spectra. High 15NH4+ affinity binding site exists in the Hybrid-1 type of the Gquadruplex, determined by NOEs between 15NH4+ and imino protons, and there is difference in the cation
selectivity and affinity between the cation binding sites.
࠙⥴ゝࠚDNAࡣᶆ‽ᵓ㐀ࡢ஧㔜ࡽࡏࢇ௨እ࡟ࡶࠊࢢ࢔ࢽࣥሷᇶ࡟ᐩࢇࡔ㡿ᇦ࡛ࢢ࢔ࢽࣥ(G)ᅄ㔜㙐࡜࿧ࡤࢀࡿᵓ㐀ࢆᙧᡂࡍࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࠋGᅄ㔜㙐ࡣG࢝ࣝࢸࢵࢺ࡜࿧ࡤࢀࡿGሷᇶ࠿ࡽ࡞ࡿᖹ㠃ᵓ㐀ࢆᣢࡕࠊᖹ㠃㛫࡟Na+ࡸK+࢖࢜ࣥ࡞࡝ࡢ㝧࢖࢜ࣥࡀ⤖ྜ࡛ࡁࡿࢧ࢖ࢺࡀᏑᅾࡍࡿࠋ
ࣄࢺࢸ࣓ࣟ࢔㓄ิࢆࡶࡘDNA࢜ࣜࢦࢾࢡࣞ࢜ࢳࢻTel26㸦d[AAAGGG(TTAGGG)3AA]㸧ࡣࠊ2ࡘࡢ
Na+࢖࢜ࣥ࡜⤖ྜࡋ࡚BasketᆺGᅄ㔜㙐㸦Tel26-2Na+㸧ࢆᙧᡂࡍࡿࡀࠊ2ࡘࡢK+࢖࢜ࣥ࡜⤖ྜࡍࡿ࡜Hybrid-1ᆺGᅄ㔜㙐㸦Tel26-2K+㸧ࢆᙧᡂࡍࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿ1㸦Fig. 1㸧ࠋ⤖ྜࡍࡿ㝧࢖࢜ࣥࡢ༙ᚄࡢ㐪࠸ࡣGᅄ㔜㙐ࡢᵓ㐀ኚ໬ࢆᘬࡁ㉳ࡇࡍࡀࠊGᅄ㔜㙐ෆ࡟2ࡘ࠶ࡿ⤖ྜࢧ࢖ࢺ㸦A- andB-site in Fig. 1㸧࡬ࡢ㝧࢖࢜ࣥࡢぶ࿴ᛶࡢ㐪࠸ࡸࠊࡑࢀࡽࡢࢧ࢖ࢺࡢ㝧࢖࢜ࣥ㑅ᢥᛶ࡟ࡘ࠸࡚ࡣሗ
࿌ࡀ࡞࠸ࠋ㝧࢖࢜ࣥ⤖ྜ࡟ࡼࡗ࡚⏕ࡌࡿGᅄ㔜㙐ᵓ㐀ࡢከᆺᛶࡣࠊGᅄ㔜㙐ࢆ࢔ࣉࢱ࣐࣮࡜฼⏝ࡍࡿࡼ࠺࡞⏕≀ᕤᏛⓗ࡞◊✲࡟࠾࠸࡚㔜せ࡛࠶ࡿࠋᮏ◊✲࡛ࡣࠊNa+ࡸK+࢖࢜ࣥ࡟ຍ࠼࡚ࠊ
15NH +࢖࢜ࣥࢆ⏝࠸࡚ࠊGᅄ㔜㙐࡬ࡢ࢖࢜ࣥࡢ⤖ྜ࡜ゎ㞳ࢆNOESYࢫ࣌ࢡࢺࣝ࡟⌧ࢀࡿ໬Ꮫ஺᥮
4ࡢࢩࢢࢼࣝ࡟ࡼࡗ࡚ゎᯒࡋࠊ2ࡘࡢ㝧࢖࢜ࣥ⤖ྜࢧ࢖ࢺࡢ≉ᚩࢆ᫂ࡽ࠿࡟ࡋࡓࠋ

Fig. 1: Hoogsteen hydrogen bonds of G-quartet and schematic structures of G-quadruplex.
ࢢ࢔ࢽࣥᅄ㔜㙐, ࢸ࣓ࣟ࢔, ໬Ꮫ஺᥮‫࠾ࡃࡓࡽࡴࡽ࡚ۑ‬㸪࠿࡞࠾ࡾࡅࢇࡌ

－ 226 －

࠙⤖ᯝ࣭⪃ᐹࠚTel26-2Na+࡟ᑐࡋ࡚K+࢖࢜ࣥࢆຍ࠼ࡿ࡜ࠊTel26-2Na+ࡢ࢖࣑ࣀࣉࣟࢺࣥࢩࢢࢼࣝ
ࡀῶᑡࡋࠊTel26-2K+࡜ࡣ໬Ꮫࢩࣇࢺࡢ␗࡞ࡿ୍⤌ࡢ࢖࣑ࣀࣉࣟࢺࣥࢩࢢࢼࣝࡀほ ࡉࢀࡓ㸦Fig.
2ࡢ‫ۻ‬㸧ࠋࡇࢀࡣTel26࡟Na+࡜K+ࡀ1ಶࡎࡘ⤖ྜࡋࡓTel26-Na+, K+࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋࡉࡽ࡟K+
࢖࢜ࣥࢆຍ࠼ࡿ࡜Tel26-2K+ࡢࢩࢢࢼࣝࡢᙉᗘࡀୖ᪼ࡋࡓࠋNOESYࢫ࣌ࢡࢺࣝ࡟ࡣTel26-Na+, K+
࡜Tel26-2K+ࡢࢩࢢࢼࣝ࡜ࡢ㛫࡟໬Ꮫ஺᥮ࡢࢡࣟࢫࣆ࣮ࢡࡀほ ࡉࢀࡓࡀࠊTel26-Na+, K+࡜Tel262Na+ࡢ㛫࡟ࡣほ ࡉࢀ࡞࠿ࡗࡓࠋࡇࡢࡇ࡜ࡣࠊTel26-Na+, K+ࡣࠊTel26-2K+࡜ྠࡌHybrid-1ᆺ࡛ࠊ
⤖ྜࡋࡓNa+ࡀK+࡜஺᥮ࡋ࡚࠸ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋTel26-Na+, K+ࡢ࢖࣑ࣀࣉࣟࢺࣥࡢࢩࢢࢼࣝ
ᮏᩘ࡜Tel26-2K+࡜ࡢ஺᥮ࡢࢡࣟࢫࣆ࣮ࢡ࠿ࡽࠊGᅄ㔜㙐ෆࡢ2ࡘࡢ⤖ྜࢧ࢖ࢺࡢ࠺ࡕࡢ࡝ࡕࡽ࠿
࡟K+࢖࢜ࣥࡀ㑅ᢥⓗ࡟⤖ྜࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡍ࡞ࢃࡕࠊHybrid-1ᆺࡢᵓ㐀ᙧᡂ࡟ᚲせ࡞K+࢖࢜ࣥࡣࠊA-ࡶࡋࡃࡣB-siteࡢ࡝ࡕࡽ࠿࡟ඃඛⓗ࡟⤖ྜࡋࠊࡶ࠺୍᪉ࡢ⤖ྜࢧ࢖ࢺ࡟ࡣNa+࡜
K+࢖࢜ࣥࡢ࠸ࡎࢀࡀ⤖ྜࡋ࡚ࡶHybrid-1ᆺ࡜ࡋ࡚Gᅄ㔜㙐ᵓ㐀ࡀᏳᐃ໬ࡉࢀࡿ࡜᥎ ࡉࢀࡿࠋHybrid-1ᆺGᅄ㔜㙐࡬ࡢK+࢖࢜ࣥ⤖ྜࡢ఩⨨㑅ᢥᛶࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵ࡟ࠊ15NH4+ࢆK+࢖࢜ࣥࡢࣉ࣮ࣟࣈ࡜ࡋ࡚౑⏝ࡋࡓࠋK+࢖࡛࢜ࣥHybrid-1ᆺࢆᙧᡂࡍࡿࡇ࡜ࡀሗ࿌2ࡉࢀ࡚࠸ࡿmutTel24
㸦d[TTGGG(TTAGGG)3A] 㸧ࡣࠊ15NH4+࢖࢜ࣥᏑᅾୗ࡛ࡶGᅄ㔜㙐ࢆᙧᡂࡋࡓࠋNOESYࢫ࣌ࢡࢺ࡛ࣝࡢNOEࣃࢱ࣮ࣥࡢゎᯒࡍࡿ࡜ࠊmutTel24-2NH4+ࡣmutTel24-2K+࡜ྠࡌHybrid-1ᆺ࡛࠶ࡗࡓࠋ
࢖࣑ࣀࣉࣟࢺࣥ࡜ࡢNOEࢡࣟࢫࣆ࣮ࢡ࠿ࡽmutTel24-2NH4+ࡢ2ࡘࡢ⤖ྜࢧ࢖ࢺ࡟⤖ྜࡍࡿ15NH4+
࢖࢜ࣥࡢࢩࢢࢼࣝࡀศ㞳ࡋ࡚ほ ࡉࢀࡓࠋmutTel24-2NH4+࡟Na+࢖࢜ࣥࢆ⁲ຍࡍࡿ࡜ࠊmutTel242NH4+࡜஺᥮ࡢࢡࣟࢫࣆ࣮ࢡࢆࡶࡘࢩࢢࢼࣝࡀ᪂ࡓ࡟ほ ࡉࢀࡓࠋ஺᥮ࡢࢡࣟࢫࣆ࣮ࢡࡀほ ࡉࢀࡓࡇ࡜࡛Na+࢖࢜ࣥࡢ⁲ຍ࡛⏕ࡌࡓmutTel24- Na+, NH4+ࡶHybrid-1ᆺ࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋ
15NH +࢖࢜ࣥࡢࢩࢢࢼࣝࡣ1ᮏࡔࡅࡀほ4ࡉࢀࠊࡑࢀ࡜࢖࣑ࣀࣉࣟࢺࣥ࡜ࡢNOE࠿ࡽࠊA-site࡟ࡣ

15NH +࢖࢜ࣥࡀ⤖ྜࡋࡓࡲࡲ࡛ࠊB-site࡟Na+࢖࢜ࣥࡀ⤖ྜࡋ࡚࠸ࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋࡇࢀࡽࡢࡇ
4࡜࠿ࡽࠊࣄࢺࢸ࣓ࣟ࢔Gᅄ㔜㙐ࡣࠊA-site࡬ࡢK+࢖࢜ࣥࡢぶ࿴ᛶࡀ㧗ࡃࠊ୍᪦ࠊA-site࡟K+࢖࢜ࣥࡀ⤖ྜࡍࡿ࡜Hybrid-1ᆺࡀBasketᆺࡼࡾࡶᏳᐃ໬ࡉࢀࡿ࡜⪃࠼ࡽࢀࡿࠋ

Fig. 3: Schematic diagram interconversionsFig. 2: Imino regions of 1H NMR spectra of Tel26 in Na+

between Na+ and NH4+ of Hybrid-1-type

solution in titration experiment of K+ at 298 K.

G-quadruplexes.

References(1) Ambrus, A., et al. (2006) Human telomeric sequence forms a hybrid-type intramolecular G-quadruplex
structure with mixed parallel/antiparallel strands in potassium solution. Nucleic Acids Res. 34, 2723–2735.

(2) Luu, K. N., et al. (2006) Structure of the human telomere in K+ solution: an intramolecular (3 + 1) G-quadruplex
scaffold. J Am Chem Soc 128, 9963-9970.

－ 227 －

P40Y

4್ࢆᣦᶆ࡟ࡋࡓእ㒊ᶆ‽ἲᐃ㔞105㸦(&T105㸧ࡢᐃ⮬ື໬࡜ࡑࡢᐃ㔞⢭ᗘ࡟ࡘ࠸࡚‫ۑ‬す㷂㞝୕1㸪▼㝃ிᏊ1㸪ྜྷᮧᘯఙ2㸪ᯇ⇃ఙஓ2㸪ᮅ಴ඞኵ3㸪ᮎᯇᏕᏊ2㸪ᮡᮏ┤ᶞ1
1 ᅜ❧་⸆ရ㣗ရ⾨⏕◊✲ᡤ
2 ᰴᘧ఍♫JEOL RESONANCE
3 ᪥ᮏ㟁Ꮚᰴᘧ఍♫Automation of external calibration quantitative NMR (EC-qNMR) based on Q value andits accuracy of the quantitative values‫ۑ‬Yuzo Nishizaki1, Kyoko Ishizuki1, Hironobu Yoshimura2, Shinya Matsukuma2, Katsuo Asakura3,
Takako Suematsu2, Naoki Sugimoto1
1 National Institute of Health Sciences
2 JEOL RESONANCE Inc.
3

JEOL Ltd.
Quantitative NMR (qNMR) is a highly regarded analytical methodology for purity determination. Thismethodology has two approaches: internal and external calibration (IC-qNMR and EC-qNMR). Of the two
approaches, to obtain accurate quantitative results with EC-qNMR, 90° pulse width (pw90) calibration isnecessary before qNMR measurement for each sample. To solve the problem of constraining the operator
in front of the NMR instrument for the pw90 calibration, we developed a script that fully automates ECqNMR according to the method conditions set by the operator: “pw continuous measurement determiningpw90”í“qNMR measurement applied the calibrated pw90”. This poster presents the details of the script
and the accuracy of quantitative results for EC-qNMR employing the script.
࠙ࡣࡌࡵ࡟ࠚ
NMRࡢᛂ⟅ࡣ┦཯ᐃ⌮࡟ᚑ࠺ࠋࡍ࡞ࢃࡕ㸪ࢳ࣮ࣗࢽࣥࢢ࡜࣐ࢵࢳࣥࢢ㸦T&M㸸Tuning andMatching㸧࡟ࡼࡾ㸪NMRࡢ᳨ฟࢥ࢖ࣝ㸦ࣉ࣮ࣟࣈ㸧ࡀ ᐃᑐ㇟᰾ࡢඹ㬆࿘Ἴᩘ࡟ྠㄪࡍࡿ࡜ࡁ࡟
㝈ࡾ㸪ࠕࣃࣝࢫᖜ㸦pw㸸pulse width㸧ࣆ࣮ࢡ㠃⥺㸭ࣉࣟࢺࣥᩘ㸭ࣔࣝ⃰ᗘࠖࡣࣉ࣮ࣟࣈᅛ᭷ࡢ
್㸦Q್㸧࡜࡞ࡿࠋ2ᮏࡢNMR⟶ࢆ⏝࠸࡚EC-qNMRࢆᐇ᪋ࡋࡓሙྜ㸪୧⪅ࡢ㛵ಀᛶࡣ௨ୗࡢᘧ
㸦1㸧࡛⾲ࡍࡇ࡜ࡀ࡛ࡁࡿࠋ
‫ܣ‬୅ ‫ܪ‬େ ‫ݓ݌‬90୅
××   㸦1㸧‫ܿ݊݋ܥ‬.୅ = ‫ܿ݊݋ܥ‬.େ ×‫ܣ‬େ ‫ܪ‬୅ ‫ݓ݌‬90େ
ࡇࡇ࡛㸪Conc.㸪ࣔࣝ⃰ᗘ㸦mol/L㸧㸹A㸪ࣆ࣮ࢡ㠃✚㸹H㸪A࡟⏤᮶ࡍࡿࣉࣟࢺࣥᩘ㸹pw90㸪90r
ࣃࣝࢫᖜ㸦sec㸧㸹ῧᏐA㸪ศᯒ✀㸹ῧᏐC㸪ᇶ‽≀㉁㸦ෆ㒊ᶆ‽ࡲࡓࡣእ㒊ᶆ‽㸧ࠋ
EC-qNMR࡛ࡣ㸪ศᯒ✀࡜ᇶ‽≀㉁ࡀ␗࡞ࡿNMRヨᩱ⟶࡟࠶ࡿࡓࡵ㸪ࡑࢀࡒࢀࡢNMRヨᩱ⟶࡛㸪ヨᩱࡢᑟ㟁ᛶࡸpw90ࡀ␗࡞ࡿࠋࡑࡢࡓࡵ㸪EC-qNMR࡛ṇ☜࡞ᐃ㔞⤖ᯝࢆᚓࡿࡓࡵ࡟ࡣ㸪qNMR ᐃࡢ๓࡟pw90ࢆᰯṇࡋ㸪ࡇࡢᰯṇࡋࡓpw90ࢆqNMR ᐃ᮲௳࡟཯ᫎࡉࡏࡿࡇ࡜ࡀ㔜せ࡛
࠶ࡿ1, 2)ࠋࡓࡔࡋ㸪ヨᩱᩘࡀከ࠸࡜ࡁࡣ࣮࢜࣌ࣞࢱࡀpw90ᰯṇࡢࡓࡵ࡟NMR⿦⨨࡟ᣊ᮰ࡉࢀࡿ࡜
እ㒊ᶆ‽ἲ㸪┦཯ᐃ⌮㸪ࣃࣝࢫᖜᰯṇ‫࠺ࡒ࠺ࡺࡁࡊࡋ࡟ۑ‬㸪࠸ࡋ࡙ࡁࡁࡻ࠺ࡇ㸪ࡼࡋࡴࡽࡦࢁࡢࡪ㸪ࡲࡘࡃࡲࡋࢇࡸ㸪࠶ࡉࡃࡽ࠿ࡘ࠾㸪ࡍ࠼ࡲࡘࡓ࠿ࡇ㸪ࡍࡂࡶ࡜࡞࠾ࡁ

－ 228 －

࠸࠺ၥ㢟ࡀ࠶ࡾ㸪EC-qNMRࡢᐇ⏝໬࡟ྥࡅࡓㄢ㢟࡜࡞ࡗ࡚࠸ࡿࠋࡑࡇ࡛ᮏ◊✲ࡣணࡵ࣮࢜࣌ࣞࢱࡀタᐃࡋࡓᐃ᮲௳࡟ᚑ࠸㸪pw90ᰯṇ㹼qNMR

ᐃࢆ⮬ື໬ࡍࡿ

ࢫࢡࣜࣉࢺࢆ㛤Ⓨࡋࡓࡢ࡛㸪ࡑࡢᴫせ࡟ࡘ࠸࡚ㄝ᫂ࡍ
ࡿࠋࡲࡓ㸪ࡇࡢ⮬ື ᐃࢫࢡࣜࣉࢺࢆ⏝࠸ࡓEC-qNMRࡢᐃ㔞⢭ᗘ࡟ࡘ࠸࡚ࡶⓎ⾲ࡍࡿࠋ࡞࠾㸪㛤Ⓨࡋࡓ⮬ືᐃࢫࢡࣜࣉࢺࡣ᪥ᮏ㟁Ꮚ〇JNM-ECAཬࡧECZศග
ィ㸦Delta version 5௨㝆㸧࡟ᑐᛂࡋࡓࡶࡢ࡛࠶ࡿࠋ
⮬ື࠙⮬ᐃࢫࢡࣜࣉࢺࡢᴫせࠚ

NMR࡛ࡣ↷ᑕ୰ᚰࡢࣆ࣮ࢡᙉᗘࢆpw࡟ᛂࡌ࡚ࣉࣟ
ࢵࢺࡍࡿ࡜㸪ῶ⾶ࡍࡿṇᘻἼࡀᥥ࠿ࢀࡿ3)ࠋࡇࡢ≉ᛶࢆ฼⏝ࡋ࡚㸪⮬ື ᐃࢫࢡࣜࣉࢺࡢpw90ᰯṇ࡟ࡣ㸪ศගィࡀ⮬ືィ⟬ྍ⬟࡞࣮࢝ࣈࣇ࢕ࢵࢸ࢕ࣥࢢ㸦CF㸧ἲࢆ᥇⏝ࡋࡓ4)ࠋFig. 1࡟⮬ື ᐃࢫࢡࣜࣉࢺࢆ౑⏝ࡋࡓ㝿ࡢศගィࡢෆ㒊ฎ⌮ࢆ♧ࡍࠋヨᩱࡣ1.0 mg/mLࡢࢪ࣓ࢳࣝࢫࣝ࣍ࣥ㸦in DMSO-d6㸧ࢆ⏝࠸ࡓࠋࡲࡎ㸪✚⟬1ᅇࡢ
1H

ᐃࢆ⾜࠸㸪ࢫ࣌ࢡࢺࣝ୰ࡢ᭱ࡶᙉᗘࡢᙉ࠸ࣆ࣮ࢡ

ࢆ᥈ࡋ㸪pw㐃⥆ ᐃࡢ↷ᑕ୰ᚰ࡟タᐃࡍࡿࠋࡇࡢ࡜ࡁ
ࡢࢧ࣮ࢳ⠊ᅖࢆ࣮࢜࣌ࣞࢱࡀ௵ព࡟㑅ᢥ࡛ࡁࡿࡼ࠺
࡟㸪search offsetཬࡧsearch sweepࡢࣃ࣓࣮ࣛࢱࢆタࡅࡓ
㸦Fig. 1࡛ࡣDMSO-d5 ࡀ↷ᑕ୰ᚰ࡜࡞ࡿࡼ࠺࡟search
offsetཬࡧsearch sweepࢆタᐃࡋ࡚࠸ࡿ㸧ࠋḟ࡟࣮࢜࣌ࣞࢱࡀタᐃࡋࡓࢹ࣮ࢱ㛫㝸࡟ᚑࡗ࡚pw㐃⥆ ᐃࢆ⾜࠸㸪඲ࢫࣛ࢖ࢫࢹ࣮ࢱ࠿ࡽ᭱ࡶᙉᗘࡢᙉ࠸ࣆ࣮ࢡࢆᣢࡘࢫ
ࣛ࢖ࢫࢹ࣮ࢱࢆᢳฟࡍࡿ㸦Fig. 1࡛ࡣࢫࣛ࢖ࢫࢹ࣮ࢱ3࡜࡞ࡿ㸧ࠋࡇࡢࢫࣛ࢖ࢫࢹ࣮ࢱࢆᇶ‽࡟ࡋ࡚㸪඲ࢫࣛ࢖ࢫࢹ࣮ࢱ࡟ᑐࡍࡿ఩┦⿵ṇ᮲௳ࢆỴᐃࡍࡿࠋ఩┦⿵ṇࡋࡓ඲ࢫࣛ࢖ࢫࢹ࣮ࢱࢆ࢔ࣞ࢖ࢹ࣮ࢱ࡜ࡋ࡚ᢅࡗ࡚
CFࢆ⾜࠺ࠋ᭱ᚋ࡟ࡇࡢCF࡛ᚓࡽࢀࡓpw90ࢆ཯ᫎࡋࡓ
qNMR

ᐃࢆ⾜࠸㸪⮬ືᐃࢆ⤊஢ࡍࡿࠋDeltaࢯࣇࢺ࢙࢘࢔ୖࡢࣃ࣓࣮ࣛࢱタᐃ⏬㠃ࡣᙜ᪥࡟♧ࡍࠋ࠙⮬⮬ືᐃࢫࢡࣜࣉࢺࢆ⏝࠸ࡓEC-qNMRࡢࡢ⢭ᗘࠚศᯒ✀࡟Ᏻᜥ㤶㓟㸦ㄆド⣧ᗘ್㸸99.8%㸧㸪እ㒊ᶆ‽
࡟3⃰ᗘࡢࢪ࣓ࢳࣝࢫࣝ࣍ࣥ㸦ㄆド⣧ᗘ್㸸99.9%㸧ࢆ⏝࠸࡚㸪⮬ື ᐃࢫࢡࣜࣉࢺࢆ⏝࠸ࡓEC-qNMRࢆᐇ᪋
ࡋࡓࠋ3⃰ᗘࡢࢪ࣓ࢳࣝࢫࣝ࣍ࣥ࠿ࡽ್௜ࡅࡓᏳᜥ㤶㓟ࡢ⤯ᑐ⣧ᗘࡣ㸪99.7 ± 0.6%࡛࠶ࡾ㸪Ᏻᜥ㤶㓟ࡢㄆド⣧ᗘ್࡜Ⰻዲ࡟୍⮴ࡋࡓ㸬ࢹ࣮ࢱࡢヲ⣽ࡣᙜ᪥࡟♧ࡍࠋ
࠙ཧ
ཧ⪃ᩥ⊩ࠚ
1)
2)

Burton et al., Anal. Chem., 77, 3123í3131 (2005)
Nishizaki et al., Anal. Chem., 93, 2733í2741 (2021)

3)

Keifer. Concepts Magn. Reason., 11, 165í180 (1999)

4)

Kurimoto et al., Chem. Lett., 34, 540í541 (2005)－ 229 －

Fig. 1 Spectrometer behavior when performing
EC-qNMR employing the script. The sample is
1.0 mg/mL dimethylsulfone in DMSO-d6. The
spectrometer was JNM-ECZ600R/S1 (600.67
MHz) equipped cryogenic UltraCOOL (CH)probe regulated at 25 °C.

P41

PFG NMRἲ䛻䜘䜛䝅䞁䝆䜸䝍䜽䝏䝑䜽䝫䝸䝇䝏䝺䞁䛻䛚䛡䜛Ẽయᣑᩓ≉ᛶ䛾ホ౯䕿ྜྷỈ㻌 ᗈ᫂㻌ྡྂᒇᕤᴗ኱Ꮫ኱Ꮫ㝔㻌 ᕤᏛ◊✲⛉㻌 ᕤᏛᑓᨷ㻌 ⏕࿨ᛂ⏝໬Ꮫ⣔䝥䝻䜾䝷䝮㻌 䝋䝣䝖䝬䝔䝸䜰䝹ศ㔝㻌

Temperature-dependent of the gas diffusion properties in syndiotactic polystyrenes
containing various crystal phases by PFG NMR‫ۑ‬Hiroaki YOSHIMIZU
Field of Soft Materials, Life Science and Applied Chemistry Program,
Graduate School of Engineering, Nagoya Institute of Technology
Alpha and mesophase crystalline phases containing syndiotactic polystyrene samples were prepared, and amagnetic field gradient pulse NMR method was applied to investigate the temperature dependence of theself-diffusion coefficient of the gas in the system. From the observed data in this study, some unique gastransport properties of crystals of syndiotactic polystyrene were pointed out.
䛆⥴ゝ䛇㻌 䜟䜜䜟䜜䛿䠈ඃ䜜䛯Ẽయศ㞳⬟䛸㧗㏱㐣ᛶ䜢ྠ᫬䛻Ⓨ⌧䛩䜛ྍ⬟ᛶ䛜ᮇᚅ䛥䜜䜛䠈㧗ᗘ䛻⛛ᗎ໬䛥䜜䛯Ẽయᣑᩓ⤒㊰䜢ᥦ౪䛩䜛㧗ศᏊ⤖ᬗయ䛾Ẽయ㍺㏦≉ᛶ䛻䛴䛔䛶᳨ウ䛧䛶䛔䜛䚹䛩䛺䜟䛱䠈⤖ᬗᵓ㐀䜢ᵓᡂ䛩䜛ศᏊ㛫䛾“䛩䛝㛫”䜢Ẽయศ㞳䛻ᛂ⏝䛩䜛ヨ䜏䛷䛒䜛䚹ከ䛟䛾㧗ศᏊ⤖ᬗయ䛷䛿䠈つ๎ṇ䛧䛔⧞䜚㏉䛧䝁䞁䝩䝯䞊䝅䝵䞁䜢䛸䛳䛯ศᏊ㙐䛜ᯘ❧䛩䜛จ㞟ᵝែ䛺䛾䛷䠈㛗㍈᪉ྥ䛜ᐃ⩏䛥䜜䜛䚹Ẽయᣑᩓ⤒㊰䜢ᥦ౪䛩䜛ศᏊ㙐㛫㝽䛿㛗㍈᪉ྥ䛻ἢ䛳䛶㐃⥆ⓗ䛻䛴䛺䛜䜚䠈୍✀䛾“䝘䝜䝏䝱䝛䝹”䛸ぢ೴䛫䜛䜘䛖䛺ᚤ✵㛫䛸䛺䜛ྍ⬟ᛶ䛜㧗䛔䚹䝅䞁䝆䜸䝍䜽䝏䝑䜽䝫䝸䝇䝏䝺䞁㻔SPS㻕䛾D䛚䜘䜃䝯䝌䝣䜵䜲䝈⤖ᬗ䛾ศᏊ㙐㛫㝽䛿䠈ẚ㍑ⓗᑠ䛥䛺ẼయศᏊ䛜ධ䜚㎸䜑䜛䝃䜲䝈䛾✵㝽䛷䛒䜛䚹Fig. 1䛻䠈㓟⣲㻛❅⣲䛾Ẽయ㏱㐣ಀᩘẚ㻔ศ㞳≉ᛶ㻕䛾ᗘ౫Ꮡ䜢♧䛩䚹T(A-M)䛿䝯䝌䝣䜵䜲䝈⤖ᬗྵ᭷ヨᩱ䠈D-RT䛿D⤖ᬗྵ᭷ヨᩱ䠈ASPS䛿㠀ᬗヨᩱ䜢ᣦ䛧䛶䛔䜛䚹ASPS䛿 ᗘୖ᪼䠈䛩䛺䜟䛱㏱㐣ᛶ䜢ྥୖ䛥䛫䜛䜋䛹ศ㞳≉ᛶ䛜ୗ䛜䜛䠈䛔䜟䜖䜛䝖䝺䞊䝗䜸䝣䛾㛵ಀ䜢♧䛧䠈୍⯡䛾↓ᐃᙧ㧗ศᏊ⭷䛸ྠ䛨ഴྥ䜢♧䛧䛯䚹䛣䜜䛻ᑐ䛧䠈⤖ᬗᵓ㐀ᚓ䜢᭷䛩䜛ヨᩱ䛷䛿䠈㏱㐣䛸ศ㞳䛾ྠ᫬ྥୖ䛜䜏䜙䜜䠈≉䛻T(A-M) 䛿䛚䜘䛭60 Υ௨ୖ䛷ศ㞳≉ᛶ䛾ⴭ䛧䛔ྥୖ䛜ண
䛣䛾

䛥䜜䜛䚹

ᗘ౫Ꮡ䛿ྍ㏫ⓗ䛷䠈໬Ꮫⓗ䛺ኚ໬䛷䛿䛺䛟䠈ᒁᡤศᏊ㐠ື䛾≉ᚩⓗ䛺䛶䠈ᣑᩓಀᩘ䛾ᗘ౫Ꮡ䛻ᅉ䜛䛸⪃ᐹ䛥䜜䜛䚹䛧䛯䛜䛳ᗘ౫Ꮡᛶ䛾ホ౯䛿㔜せ䛷䛒䜚䠈ᮏ◊✲䛷䛿PFG NMRἲ䛾㐺⏝ୖ㓟⣲䜔❅⣲䜢ᑐ㇟䛻䛿䛷䛝䛪䠈
1H NMRほྍ⬟䛺CH4䛸n-C4H10䜢⏝䛔䛯䚹PFG NMR, syndiotactic polystyrene, gas diffusion properties.
‫ࡁ࠶ࢁࡦ ࡎࡳࡋࡼۑ‬－ 230 －

Fig. 1 Permselectivity of O2 and N2 vs. temp.

䛆ᐇ㦂䛇㻌 ฟග⯆⏘(ᰴ)䜘䜚౪୚䛥䜜䛯SPS䛿䠈䛭䛾䜎䜎⏝䛔䛯䚹280 Υ௨ୖ䛷䝥䝺䝇〇⭷䛧䛯䛾䛱䠈ịỈ䜈ᢞධ䛧䛶㠀ᬗ⭷ 㻔ASPS㻕 䜢ᚓ䛯䚹ASPS䜢䝖䝹䜶䞁䛻ᾐₕ䛧䛶䛣䜜䛜ໟ᥋䛥䜜䛯G⤖ᬗ䜢ᙧᡂ䛥䛫䛯䛾䛱䠈䜰䝉䝖䞁䠈䝯䝍䝜䞊䝹䛾㡰䛷஧ẁ㝵䛻ᾐₕฎ⌮䜢᪋䛧䛶䠈䝖䝹䜶䞁䛜᏶඲䛻⬺㞳䛧䛯䝯䝌䝣䜵䜲䝈⤖ᬗྵ᭷⭷ 㻔T(A-M)㻕 䜢ᚓ䛯䚹272 Υ䛷䝥䝺䝇〇⭷䛧䠈ᐊ 䜎䛷ᚎ෭䛧䛶D⤖ᬗྵ᭷⭷ 㻔D-RT㻕 䜢ᚓ䛯䚹㐺ษ䛺኱䛝䛥䛻⿢᩿䛥䜜䛯ヨᩱ∦䜢䠈䝔䝣䝻䞁〇䝞䝹䝤䜻䝱䝑䝥䛜௜䛔䛯◳㉁䜺䝷䝇〇⪏ᅽヨᩱ⟶䠄ᕷ㈍ရ䠅䛻㐺㔞ワ䜑䛯䚹ᐊୗ䛷༑ศ᫬㛫┿✵ᘬ䛝䜢䛧䛯䛾䛱䠈ᡤᐃᅽ䛾CH4䜎䛯䛿n-C4H10䜢ᑟධ䛧䠈䛣䜜䜙䛾⣔୰䛻䛚䛡䜛⮬ᕫᣑᩓಀᩘ䜢1H PFG NMR䛻䜘䛳䛶Ỵᐃ䛧䛯䚹㧗ᙉᗘPFG (~13 [T/m]) 䛜ᢅ䛘䜛௙ᵝ䛾JEOL ECA600 NMRศගィ䜢⏝䛔䛯䚹䛆⤖ᯝ䛸⪃ᐹ䛇㻌 ඛ䛪䠈SPSྛヨᩱ䛻཰╔䛧䛯CH4䛸n-C4H10䛾㐠ືᛶ䛻㛵䛧䛶1H NMR䝇䝨䜽䝖䝹䛾䝢䞊䜽⥺ᖜ䛛䜙ᐃᛶⓗ䛺ホ౯䜢ヨ䜏䛯䚹䛩䜉䛶䛾ヨᩱ䛸Ẽయ✀䛷⥺ᖜ䛿 ᗘ䛸䛸䜒䛻ῶ䛨䛯䛾䛷䠈཰╔Ẽయ䛾㐠ືᛶホ౯䛿㆟ㄽྍ⬟䛸ุ᩿䛧䛯䚹n-C4H10䛾⥺ᖜ䛿3ヨᩱ㛫䛷኱䛝䛺㐪䛔䛿䛺䛟䠈⤖ᬗ┦䛾Ꮡᅾ䛜䛣䜜䛾㐠ືᛶ䛻୚䛘䜛ᙳ㡪䛿ᑡ䛺䛔䛸ᛮ䜟䜜䜛䚹୍᪉䠈D-RT䛸T(A-M)䛻཰╔䛧䛯CH4䛾⥺ᖜ䛿䠈
ASPS䛷䛾䜒䛾䛻ẚ䜉඲ ᗘ⠊ᅖ䛻䜟䛯䜚ᑠ䛥䛔್䛷䛒䛳䛯䚹䛣䜜䜙䛾ほ ஦ᐇ䛿䠈D䛚䜘䜃䝯䝌䝣䜵䜲䝈⤖ᬗ䛿CH4䜢㏱㐣ྍ⬟䛷䠈䛭䜜䜙䛷䛾㐠ືᛶ䛿㠀ᬗ㉁┦䛷䛾䜒䛾䜘䜚㧗䛔䛣䛸䜢♧၀䛧䛶䛔䜛䚹䜎䛯䠈T(A-M)䛷䛿⣙60 Υ௜㏆䛷⥺ᖜ䛾 ᗘ౫Ꮡ䛜᫂░䛻ኚ໬䛧䠈Fig. 1䛻♧䛧䛯O2䜔N2䛾㏱㐣䛻ᑐᛂ䛧䛯ᣲື䜢♧䛧䛯䚹T(A-M)䛾≉␗䛺ḟ䛻䠈⮬ᕫᣑᩓಀᩘ䛾ᐃ⤖ᯝᗘ≉ᛶ䛿䝯䝌䝣䜵䜲䝈⤖ᬗ䛾≉ᛶ䛻⏤᮶䛩䜛䛸ᛮ䜟䜜䜛䚹ᐃ䜢⾜䛳䛯䚹⤖ᯝ䜢Fig. 2䛻䜎䛸䜑䛯䚹䛣䜜䜢䜏䜛䛸䠈ASPS䛸D-RT䠈T(A-M)

䛻䛚䛡䜛n-C4H10䛾⮬ᕫᣑᩓಀᩘ್䛾ᗘ౫Ꮡ䛿䛔䛪䜜䜒஫䛔䛻ఝ㏻䛳䛯⤖ᯝ䛸䛺䛳䛶䛔䜛䚹≉➹䛩䜉䛝䛿䠈㠀ᬗ┦䛾䜺䝷䝇㌿⛣ ᗘ௜㏆௨ୖ䛷 ᗘኚ໬䛜⦆៏䛻䛺䛳䛶䛔䜛䛣䛸䛷䛒䜛䚹⣔୰䛷ᣑᩓ䛩䜛Ẽయ䛾άᛶ໬䜶䝛䝹䜼䞊䛜䠈㧗ศᏊ㙐䝉䜾䝯䞁䝖䛾㐠ືᛶ䛻ᚊ䛫䜙䜜䛶䛔䜛ᵝᏊ䛜ఛ䛘䜛䚹୍᪉䠈T(AM)䛻䛚䛡䜛CH4䛾䜏඲ᗘᇦ䛻䜟䛯䜚್䛿ቑ኱䛧⥆䛡䛶䛔䛯䚹T(A-M)䛾㠀ᬗ┦䛻䛚䛡䜛㧗ศᏊ㙐䛾㐠ືᛶ䛾ኚ໬䛜཯ᫎ䛥䜜䛺䛔䜘䛖䛻ぢ䛘䜛䛾䛿䠈㧗 ᇦ䛻䛚䛡䜛䝯䝌䝣䜵䜲䝈⤖ᬗෆ䛷䛾CH4䛾ᣑᩓᛶ䛜㣕㌍ⓗ䛻ቑ኱䛧䠈㠀ᬗ┦䛻䛚䛡䜛ቑຍ⋡䛾పୗ䜢⿵䛳䛯䛯䜑䛸ᛮ䜟䜜䜛䚹䛣䛾⪃ᐹ䛿䠈Fig. 1䛻♧䛧䛯
O2䜔N2䛾㏱㐣 ᐃ⤖ᯝ䛸▩┪䛧䛺䛔䚹

Fig. 2 Arrhenius plots of self-diffusion coefficient of the CH4 and n-C4H10 in SPS samples.

－ 231 －

P42Y

14-3-3ȗ࡟ࡼࡿ㌿෗ᅉᏊFOXO3aࡢ㜼ᐖ࣓࢝ࢽࢬ࣒ࡢゎ᫂‫ۑ‬᱓ᒣ▱ஓ㸪୰ሯᑗ୍㸪ᶓᕝ┿᲍Ꮚ㸪Ἑὠගస㸪୰ᮧྣబ㸪ᮌᮧ཭⨾㸪⏣㎶ᖿ㞝㸪༓⏣ಇဢ㸪㰻⸨₶㸪బ㇂⚽⾜㸪኱⃝໷⠊
1៞᠕⩏ሿ኱Ꮫ࣭኱Ꮫ㝔⸆Ꮫ◊✲⛉2㧗࢚ࢿࣝࢠ࣮ຍ㏿ჾ◊✲ᶵᵓ࣭≀㉁ᵓ㐀⛉Ꮫ◊✲ᡤ
3៞᠕⩏ሿ኱Ꮫ࣭኱Ꮫ㝔་Ꮫ◊✲⛉Structural insights into the inhibitory mechanism of transcription factor FOXO3a
by 14-3-3ȗ
‫ۑ‬Tomoya Kuwayama1, Shoichi Nakatsuka1, Mariko Yokogawa1, Kosaku Kawatsu1, Risa Nakamura1,
Tomomi Kimura1, Mikio Tanabe2, Toshiya Senda2, Jun Saito3, Hideyuki Saya3, Masanori Osawa1
1 Grad. Sch. Pharm. Sci., Keio Univ.

 2 Structural Biology Research Center, IMSS, KEK

3 Grad. Sch. Med., Keio Univ.

FOXO3a is a transcriptional factor that induces expression of apoptosis-related proteins. In cancer cells,
FOXO3a is phosphorylated and bound by an adaptor protein, 14-3-3ȗ, dissociating from target DNA. Thisdecreases its transcriptional activity, and results in the suppression of apoptosis of cancer cells that leads tomalignancy of the cancer. However, previous studies of us and others show the binding affinity of thephosphorylated FOXO3a for DNA is comparable to that for 14-3-3ȗ. Therefore, it remains elusive how 143-3ȗ effectively dissociates FOXO3a from DNA. In this study, we have analyzed the interaction mode
between 14-3-3ȗ and phosphorylated FOXO3a by chemical shift perturbation and proposed a mechanism of
FOXO3a dissociation from DNA by 14-3-3ȗ.
࠙ᗎㄽࠚ
FOXO3aࡣࠊ࢔࣏ࢺ࣮ࢩࢫࢆಁ㐍ࡍࡿ㌿෗ᅉᏊ࡛࠶ࡿࠋከࡃࡢࡀࢇ⣽⬊࡛ࡣRasࡢ
ኚ␗ࢆ㉳※࡜ࡍࡿࣜࣥ㓟໬ࢩࢢࢼࣜࣥࢢࡀ ஹ 㐍 ࡋ ࡚ ࠾ ࡾ ࠊ ࡑࡢୗ ὶ ࡟ ఩ ⨨ ࡍ ࡿ
FOXO3aࡣࠊ」ᩘಶᡤ࡛ࣜࣥ㓟໬ࢆཷࡅࡿࠋ
ࣜࣥ㓟໬ࡉࢀࡓFOXO3aࡣࠊࡀࢇ⣽⬊࡛㧗
Ⓨ⌧ࡍࡿ࢔ࢲࣉࢱ࣮ࢱࣥࣃࢡ㉁14-3-3ȗ࡜⤖ྜࡋ࡚ᶆⓗDNA࠿ࡽゎ㞳ࡋࠊ㌿෗ᅉᏊ࡜ࡋ࡚ࡢᶵ⬟ࡀపୗࡍࡿ(㻲㼕㼓㻚㻌㻝)ࠋࡇࢀ࡟ࡼࡾ
ࡀࢇ⣽⬊ࡢ࢔࣏ࢺ࣮ࢩࢫࡀᢚไࡉࢀࠊࡀࢇ
ࡢᝏᛶ໬࡟ࡘ࡞ࡀࡿ(Obsil T. et al., Biochim㻲㼕㼓㻚㻌㻝㻚㻌 㻼㼔㼛㼟㼜㼔㼛㼞㼥㼘㼍㼠㼑㼐㻌㻲㻻㼄㻻㻟㼍㻌㼘㼛㼟㼑㼟㻌㼕㼠㼟㻌㼠㼞㼍㼚㼟㼏㼞㼕㼜㼠㼕㼛㼚㼍㼘㻌㼍㼏㼠㼕㼢㼕㼠㼥㻌㼎㼥㻌㼐㼕㼟㼟㼛㼏㼕㼍㼠㼕㼛㼚㻌㼒㼞㼛㼙㻌㻰㻺㻭㻌㼡㼜㼛㼚㻌㼎㼕㼚㼐㼕㼚㼓㻌㼠㼛㻌㻝㻠㻙㻟㻙㻟䃕㻌

Biophys Acta., 2011)ࠋࡋࡓࡀࡗ࡚ࠊ14-3-3ȗ࡟ࡼࡿFOXO3aࡢ㌿෗άᛶపୗࡢ࣓࢝ࢽࢬ࣒ࢆゎ࡛᫂ࡁࢀࡤࠊࡑࡢ┦஫స⏝ࢆ㜼ᐖࡍࡿ᪂つᢠࡀࢇ๣ࡢ๰〇ࡀᮇᚅ࡛ࡁࡿࠋ
ࡀࢇࣜࣥ㓟໬ࢩࢢࢼࣝ, FOXO3a, 14-3-3ȗ
ࠐࡃࢃࡸࡲ࡜ࡶࡸ㸪࡞࠿ࡘ࠿ࡋࡻ࠺࠸ࡕ㸪ࡼࡇࡀࢃࡲࡾࡇ㸪࠿ࢃࡘࡇ࠺ࡉࡃ㸪࡞࠿ࡴࡽࡾࡉ㸪ࡁࡴࡽ࡜ࡶࡳ㸪ࡓ࡞࡭ࡳࡁ࠾㸪ࡏࢇࡔ࡜ࡋࡸ㸪ࡉ࠸࡜࠺ࡌࡹࢇ㸪ࡉࡸࡦ࡛ࡺࡁ㸪࠾࠾ࡉࢃࡲࡉࡢࡾ

－ 232 －

FOXO3a ࡣ673ṧᇶ࠿ࡽ࡞ࡿࢱࣥࣃࢡ㉁࡛࠶ࡾࠊᵓ㐀㠀ᙧᡂ㡿ᇦ࡟ᣳࡲࢀࡓDNA-binding domain(DBD, residues 157-253)ࢆ᭷ࡍࡿࠋࡇࡢDBDࢆ௓ࡋ࡚ᶆⓗDNA࡟⤖ྜࡋࠊࡑࡢゎ㞳ᐃᩘ㸦Kd㸧ࡣ⣙
10-8 M࡛࠶ࡿ(㻲㼕㼓㻚㻌㻞) (Tsai K.-L. et al., Nucleic Acids Res., 2007)ࠋ
14-3-3ȗࡣ245ṧᇶ࠿ࡽ࡞ࡿࢱࣥࣃࢡ㉁࡛࠶ࡾࠊ9ᮏࡢ࣊ࣜࢵࢡࢫ࠿ࡽ࡞ࡿࢧࣈࣘࢽࢵࢺࡀ஧㔞యࢆᙧᡂࡋࠊࣜࣥ㓟໬ࡉࢀࡓSer / Thrࢆྵࡴ7ṧᇶ⛬ᗘࡢࣔࢳ࣮ࣇ࡟⤖ྜࡍࡿ(㻲㼕㼓㻚㻌㻟) (Yaffe M. B. et al.,Cell, 1997)ࠋ14-3-3ȗࡣࠊThr32࡜Ser253ࡢ2࠿ᡤࡀࣜࣥ㓟໬ࡉࢀࡓFOXO3a (dpFOXO3a)࡜⤖ྜࡋࠊࡑࡢKdࡣ⣙10-8 M࡛࠶ࡿ(Obsil T. et al., Biochemistry, 2003)ࠋࡇࢀࡲ࡛࡟14-3-3ȗ࡜ࣜࣥ㓟໬࣌ࣉࢳࢻ࡜
ࡢ」ྜయᵓ㐀ࡣከᩘሗ࿌ࡉࢀ࡚࠸ࡿࡀࠊࣜࣥ㓟໬㒊఩ࢆྵࡴᶆⓗࢱࣥࣃࢡ㉁඲య࡜ࡢ」ྜయᵓ㐀ࡣࡈࡃᑡᩘࡢሗ࿌౛ࡋ࠿࡞ࡃࠊdpFOXO3a࡜ࡢ⤖ྜᵝᘧࡶ୙࡛᫂࠶ࡿ(Killoran R. C. et al., PLoS One,2015)ࠋࡲࡓࠊdpFOXO3aࡣ14-3-3ȗ࡜DNA࡟ᑐࡍࡿ⤖ྜぶ࿴ᛶࡀ࡯ࡰྠ➼࡛࠶ࡿ࡟ࡶ㛵ࢃࡽࡎࠊ143-3ȗࡀ࠸࠿࡟ࡋ࡚dpFOXO3aࢆDNA࠿ࡽゎ㞳ࡉࡏࡿࡢ࠿ࡣ୙࡛᫂࠶ࡗࡓࠋ
ࡑࡇ࡛ᮏ◊✲࡛ࡣࠊNMR࡟ࡼࡾdpFOXO3a࡜14-3-3ȗࡢ┦஫స⏝ᵝᘧࢆゎ᫂ࡋࠊ14-3-3ȗ࡟ࡼࡿ
dpFOXO3aࡢDNA࠿ࡽࡢゎ㞳࣓࢝ࢽࢬ࣒ࡢゎ᫂ࢆ┠ᣦࡋࡓࠋ㻲㼕㼓㻚㻌㻞㻚㻌 㻔㼍㻕㻌㻰㼛㼙㼍㼕㼚㻌㼛㼒㻌㻲㻻㼄㻻㻟㼍㻌㻌 㻌 㻌 㻌 㻌 㻌 㻔㼎㻕㻌㻯㼞㼥㼟㼠㼍㼘㻌㼟㼠㼞㼡㼏㼠㼡㼞㼑㻌㼛㼒㻌㻲㻻㼄㻻㻟㼍㻙㻰㻮㻰㻌㻛㻌㻰㻺㻭㻌㻲㼕㼓㻚㻌㻟㻚㻌 㻯㼞㼥㼟㼠㼍㼘㻌㼟㼠㼞㼡㼏㼠㼡㼞㼑㻌㼛㼒㻌㻝㻠㻙㻟㻙㻟䃕㻌㼍㼚㼐㻌㼜㻿㻌㻛㻌㼜㼀㻌㼎㼕㼚㼐㼕㼚㼓㻌㼓㼞㼛㼛㼢㼑㻌࠙᪉ἲࠚ
14-3-3ȝ࡜FOXO3a (residues 1-284)ࡣࡑࢀࡒࢀ኱⭠⳦࡟࡚Ⓨ⌧ࡋ⢭〇ࡋࡓࠋdpFOXO3aࡣࠊᕷ㈍ࡢAKTࢆ⏝࠸࡚FOXO3aࢆࣜࣥ㓟໬ࡋ࡚ㄪ〇ࡋࡓࠋḟ࡟ࠊ13C, 15N࡟ࡼࡾᶆ㆑ࡋࡓFOXO3a࠾ࡼࡧ
2H, 13C, 15N࡟ࡼࡾᶆ㆑ࡋࡓ14-3-3ȗࢆࡑࢀࡒࢀㄪ〇ࡋࠊ୕㔜ඹ㬆࡟ࡼࡾ୺㙐NMRࢩࢢࢼࣝࡢᖐᒓࢆ

☜❧ࡋࡓࠋࡲࡓࠊ2H, 15Nᶆ㆑ࡋࡓdpFOXO3a࠾ࡼࡧ14-3-3ȗ࡟ᑐࡋ࡚㠀ᶆ㆑14-3-3ȗࠊdpFOXO3aࢆࡑࢀࡒࢀ⁲ᐃࡋࠊ1H-15N TROSYࡢࢫ࣌ࢡࢺࣝኚ໬ࢆゎᯒࡋࡓࠋ－ 233 －

࠙⤖ᯝࠚ

+1GS)2;2D࡬ࡢȝࡢ⁲ᐃᐇ㦂
dpFOXO3a ୖࡢ 14-3-3ȗ ⤖ྜ㒊఩ࢆㄪ࡭ࡿࡓࡵ࡟ࠊ2H, 15N ᶆ㆑ dpFOXO3a ࡢ 1H-15N TROSY ࡢࢫ࣌ࢡࢺࣝኚ໬ࢆᣦᶆ࡜ࡋ࡚ࠊ14-3-3ȗ ࡢ⁲ᐃᐇ㦂ࢆ⾜ࡗࡓ (㻲㼕㼓㻚㻌 㻠)ࠋ14-3-3ȗ ࡢῧຍ࡟క࠸ࠊ୍㒊ࡢࢩࢢࢼࣝ࡟ᙉᗘῶᑡ࣭ᾘኻ࡜᪂ࡓ࡞ࢩࢢࢼࣝࡢฟ⌧ࡀほࡉࢀࠊ୧⪅ࡀ┤᥋⤖ྜࡍࡿࡇ࡜ࡀศ

࠿ࡗࡓࠋࢩࢢࢼࣝࡀᾘኻࡋࡓṧᇶࡣࠊ14-3-3ȗ ࡀ⤖ྜࡍࡿ࡜ࡉࢀ࡚࠸ࡓࣜࣥ㓟໬㒊఩࿘㎶ࡔࡅ࡛࡞ࡃࠊከ
ࡃࡢ DBD ࡢṧᇶࢆྵࢇ࡛࠸ࡓࠋࡑࡇ࡛ࡑࢀࡽࢆ FOXO3a-DBD ࡢᵓ㐀ୖ࡟࣐ࢵࣆࣥࢢࡋࡓ࡜ࡇࢁ
DNA ⤖ྜ⏺㠃࡟Ꮡᅾࡋ࡚࠸ࡓࡇ࡜࠿ࡽࠊ14-3-3ȗ ࡣࣜࣥ㓟໬ࣔࢳ࣮ࣇࡔࡅ࡛࡞ࡃ DBD ࡜ࡶ┦஫స⏝ࡋࠊDNA ࡢ⤖ྜࢆ➇ྜⓗ࡟㜼ᐖࡍࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
ࡲࡓࠊู㏵ DBD ࡢ 1H-15N HSQC ࢆᣦᶆ࡜ࡋࡓ 14-3-3ȗ ࡢ⁲ᐃᐇ㦂࡛ࡣࠊfast exchange regime ࡛ࡢࢫ࣌ࢡࢺࣝኚ໬ࡀほ ࡉࢀࡓࠋ໬Ꮫࢩࣇࢺኚ໬ࡢ⁲ᐃ᭤⥺࡬ࡢ fitting ࠿ࡽࠊDBD ࡜ 14-3-3ȗ ࡢ
Kd ࡣ⣙ 2 M ࡜᥎ᐃࡉࢀࡓ(data not shown)ࠋ

㻌㻲㼕㼓㻚㻌㻠㻚㻌㻺㻹㻾㻌㼠㼕㼠㼞㼍㼠㼕㼛㼚㻌㼑㼤㼜㼑㼞㼕㼙㼑㼚㼠㼟㻌㼛㼒㻌㻝㻠㻙㻟㻙㻟䃕㻌㼕㼚㼠㼛㻌㻞㻴㻘㻌㻝㻡㻺㻙㼐㼜㻲㻻㼄㻻㻟㼍㻌㻔㼍㻕 㻝㻴㻙㻝㻡㻺㻌㼀㻾㻻㻿㼅㻌㼟㼜㼑㼏㼠㼞㼍㻌㼛㼒㻌㼐㼜㻲㻻㼄㻻㻟㼍㻌㼕㼚㻌㼠㼔㼑㻌㼜㼞㼑㼟㼑㼚㼏㼑㻌㼍㼚㼐㻌㼍㼎㼟㼑㼚㼏㼑㻌㼛㼒㻌㻝㻠㻙㻟㻙㻟䃕㻌㻌㻔㼎㻕 㻹㼍㼜㼜㼕㼚㼓㻌㼛㼚㻌㼠㼔㼑㻌㼍㼒㼒㼑㼏㼠㼑㼐㻌㼞㼑㼟㼕㼐㼡㼑㼟㻌㼛㼚㻌㼠㼔㼑㻌㻲㻻㼄㻻㻟㼍㻙㻰㻮㻰㻌－ 234 －

㻞㻴㻘㻝㻡㻺㻌㻝㻠㻙㻟㻙㻟䃕䜈䛾㼐㼜㻲㻻㼄㻻㻟㼍䛾⁲ᐃᐇ㦂㻌
14-3-3ȗୖࡢdpFOXO3a⤖ྜ㒊఩ࢆㄪ࡭ࡿࡓࡵ࡟ࠊ2H,15Nᶆ㆑14-3-3ȗࡢ1H-15N TROSYࡢࢫ࣌ࢡࢺ

ࣝኚ໬ࢆᣦᶆ࡜ࡋ࡚ࠊdpFOXO3aࡢ⁲ᐃᐇ㦂ࢆ⾜ࡗࡓࠋdpFOXO3aࢆῧຍ࡟క࠸ࠊ୍㒊ࡢࢩࢢࢼࣝ
࡟slow exchange regime࡛ࡢᾘኻ࣭ฟ⌧ࡀほ ࡉࢀࡓࠋࡇࢀࡽࡢṧᇶࢆ14-3-3ȗࡢ❧యᵓ㐀ୖ࡟࣐ࢵࣆࣥࢢࡋࡓ࡜ࡇࢁࠊࣜࣥ㓟໬ࣔࢳ࣮ࣇࡢ⤖ྜ㒊఩࡛࠶ࡿ⁁ࡢෆഃࡔࡅ࡛࡞ࡃࠊࡑࡢ࿘㎶࠿ࡽ⁁ࡢእഃࡢ㡿ᇦ㸦࣊ࣜࢵࢡࢫ8࡜9㸧࡟໬Ꮫࢩࣇࢺኚ໬㒊఩ࡀᗈࡀࡗ࡚࠸ࡓ(㻲㼕㼓㻚㻌㻡)ࠋ

㻲㼕㼓㻚㻌㻡㻚㻌㻹㼍㼜㼜㼕㼚㼓㻌㼛㼒㻌㼠㼔㼑㻌㼞㼑㼟㼕㼐㼡㼑㼟㻌㼛㼒㻌㻝㻠㻙㻟㻙㻟䃕㼍㼒㼒㼑㼏㼠㼑㼐㻌㼎㼥㻌㼐㼜㻲㻻㼄㻻㻟㼍㻌㼎㼕㼚㼐㼕㼚㼓㻌࠙⪃ᐹࠚᮏ◊✲ࡼࡾࠊdpFOXO3aࡣࠊࣜࣥ㓟໬ࣔࢳ࣮ࣇࡔࡅ࡛࡞ࡃDBDࡢDNA⤖ྜ⏺㠃࡟࠾࠸࡚14-3-3ȗ
ࡢ࣊ࣜࢵࢡࢫ8, 9࡜┦஫స⏝ࡍࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡾࠊ14-3-3ȗࡣࡇࡢ㒊఩࡛FOXO3aࡢDNA⤖ྜࢆ➇ྜⓗ࡟㜼ᐖࡍࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡋ࠿ࡋࠊdpFOXO3aࡣᶆⓗDNA࡜14-3-3ȗࡢ⤖ྜぶ࿴ᛶࡣྠ➼࡛࠶ࡾࠊ࠿ࡘࠊDBD࡜14-3-3ȗࡢ⤖ྜぶ࿴ᛶࡣDBD࡜DNAࡢ⤖ྜぶ࿴ᛶࡼࡾ㢧ⴭ࡟ప࠸ࠋࡑࢀ࡟
ࡶ㛵ࢃࡽࡎࠊ14-3-3ȗࡀdpFOXO3aࢆᶆⓗDNA࠿ࡽ➇ྜⓗ࡟ゎ㞳ࡉࡏࡿࠋᡃࠎࡣࡑࡢ࣓࢝ࢽࢬ࣒࡜
ࡋ࡚ࠊ14-3-3ȗࡣࠊdpFOXO3aࡢDBD୧ᮎ➃ഃ࡟1ಶࡎࡘᏑᅾࡍࡿࣜࣥ㓟໬ࣔࢳ࣮ࣇ࡟ࡼࡾ㧗ぶ࿴ᛶ࡛ࡘ࡞ࡂ␃ࡵࡽࢀࡿࡇ࡜࡟ࡼࡗ࡚DBD࿘㎶࡟ᖖ࡟㧗⃰ᗘ࡛Ꮡᅾࡋࠊ14-3-3ȗ࡜DBD࡜ࡢ⤖ྜࡀపぶ࿴ᛶ࡛࠶ࡗ࡚ࡶDNAࡢ➇ྜⓗ࡞ゎ㞳ࢆྍ⬟࡜ࡍࡿ࡜࠸࠺ࣔࢹࣝࢆᥦၐࡍࡿ(㻲㼕㼓㻚㻌㻢)ࠋ

㻲㼕㼓㻚㻌㻢㻚㻌㻼㼞㼛㼜㼛㼟㼑㼐㻌㼙㼛㼐㼑㼘㻌㼛㼒㻌㼐㼜㻲㻻㼄㻻㻟㼍㻌㼐㼕㼟㼟㼛㼏㼕㼍㼠㼕㼛㼚㻌㼒㼞㼛㼙㻌㻰㻺㻭㻌㼎㼥㻌㻝㻠㻙㻟㻙㻟䃕㻌㼎㼕㼚㼐㼕㼚㼓㻌－ 235 －

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=   -7%)7%0!$ &"!    ,-/%<%1%)7%0     -/8',-)7%0      #-6,%57!)7%0 %#6

 -<%1373)7%0!$ &"!      － 237 －

P44Y

OHಙྕࢆࡶ࡜࡟ࡋࡓJ couplingࡢ‫⸨ۑ‬ᮧ㐶 㸪ෆᾏ༤᫂1,ᐃ࠾ࡼࡧ஧㠃ゅࡢィ⟬➲ᕝᣑ᫂11ᰴᘧ఍♫JEOL RESONANCE

Measurement of J coupling constants related to the hydroxyl protons and the dihedral
angles estimation‫ۑ‬Haruka Fujimura1, Hiroaki Utsumi1, Hiroaki Sasakawa1
1 JEOL RESONANCE Inc.

The hydroxyl proton signals of sucrose are difficult to be detected by the standard NMR measurement
condition, however it is known that those are observed in the mixture of water and acetone-d6 solution at low
temperature. Since the conformation of sucrose in aqueous solution is considered to be affected by thehydrogen bond surrounding the hydroxy group, it would be beneficial for structure analysis to investigate itsdihedral angle including hydroxy group. In this study, we evaluated the optimal methods for the J coupling
constants measurement related to the hydroxyl protons, and estimated the dihedral angles, H-C-O-H and CC-O-H, from the J coupling constants.

Ỉ㓟ᇶࡀྵࡲࢀࡿศᏊࡢỈ⁐ᾮ୰ࡢ❧యᵓ㐀࡟ࡘ࠸࡚ࡣࠊỈ㓟ᇶ࿘ࡾࡢ❧యᵓ㐀ࡢ▱ぢࡀᚓࡓ࠸࡜࠸࠺せồࡀ࠶ࡿࠋࡇࢀࡣ⁐፹㸦Ỉ㸧࡜ࡢỈ⣲⤖ྜ➼ࡢ┦஫స⏝࡟ࡼࡾỈ㓟ᇶ࿘㎶ࡢ❧యᵓ㐀ࡀᙳ㡪ࢆཷࡅࡿࡇ࡜ࡀ࠶ࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿ࠿ࡽ࡛࠶ࡿࠋ㏻ᖖࡢNMR ᐃ᮲௳࡛ࡣほࡀ㞴ࡋ࠸Ỉ㓟ᇶࡢಙྕ࡛࠶ࡿࡀࠊ஧⢾࡛࠶ࡿࢫࢡ࣮ࣟࢫ
㸦Fig.1㸧ࢆỈ㸫㔜࢔ࢭࢺࣥΰྜ⁐፹࡟⁐࠿ࡋ࡚పᐃࢆ⾜࠺ࡇ࡜࡛ࠊỈ㓟ᇶࣉࣟࢺࣥಙྕࡀほ ࡛ࡁࡿࡇ࡜ࡀ

Fig. 1. Sucrose
OH signalsሗ࿌ࡉࢀ࡚࠸ࡿ1ࠋỈ⁐ᾮ୰࡛ࡣࠊࢫࢡ࣮ࣟࢫࡢỈ㓟ᇶࡀỈ࡜┦஫స⏝ࡍࡿ࡜⪃࠼ࡽࢀ࡚࠾ࡾࠊỈ㓟ᇶ࿘㎶ࡢỈ⣲⤖ྜࡀỈ⁐ᾮ୰ࡢࢫࢡ࣮ࣟࢫࡢ❧యᵓ㐀࡟㛵୚ࡋ࡚࠸ࡿ
࡜᥎ᐹࡉࢀࡿࠋࡲࡓࠊほ ࡉࢀࡓỈ㓟ᇶࣉࣟࢺࣥಙྕࡢ
NOE࠿ࡽ᰾㛫㊥㞳ࡢ᝟ሗࢆồࡵࡿࡔࡅ࡛࡞ࡃࠊJ࢝ࢵࣉࣜࣥࢢࢆㄞࡴࡇ࡜࡟ࡼࡾࠊỈ㓟ᇶ࿘㎶ࡢ஧㠃ゅ㸦H-C-O-H

Fig. 2. 1H spectrum with Perfect Echo࠾ࡼࡧC-C-O-H㸧ࡀồࡵࡽࢀࡿࡇ࡜ࡣ௨๓ࡼࡾᥦ᱌ࡉࢀWATERGATE࡚࠸ࡿࠋ௒ᅇࠊᡃࠎࡣỈ㓟ᇶ࿘㎶ࡢ஧㠃ゅ㸦H-C-O-H࠾ࡼ

50 mM sucrose in the water andࡧC-C-O-H㸧ࡢ᭱㐺࡞ồࡵ᪉࡟ࡘ࠸࡚ࠊಙྕࡢᖐᒓࡶྵ

acetone-d6 solution at -20dC, collectedࡵࠊᨵࡵ᳨࡚ウࢆ⾜ࡗࡓࠋby JNM-ECZL500R.

ࢧࣥࣉࣝ࡜ࡋ࡚ࡣࠊࢫࢡ࣮ࣟࢫࢆỈ㸫㔜࢔ࢭࢺࣥΰྜ
⁐፹㸦Ỉ㸸㔜࢔ࢭࢺࣥ㸻2:3㸧࡟⁐ゎࡋࡓࡶࡢࢆ౑⏝ࡋࡓࠋࣉࣟࢺࣥࡢ஺᥮㏿ᗘࢆపୗࡉࡏࡿࡓࡵࠊ
-20Υࡢప ᮲௳࡛Ỉ㓟ᇶࣉࣟࢺࣥࡢほ ࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝࠊ5.3㹼6.5 ppm௜㏆࡟Ỉ㓟ᇶ⏤᮶࡜Ỉ㓟ᇶ㸪J࢝ࢵࣉࣜࣥࢢ, ஧㠃ゅ‫࠿ࡿࡣࡽࡴࡌࡩۑ‬㸪࠺ࡘࡳࡦࢁ࠶ࡁ, ࡉࡉ࠿ࢃࡦࢁ࠶ࡁ

－ 238 －

ࡉࢀࡓࢫࢡ࣮ࣟࢫࡢಙྕࡢᖐᒓࢆ⾜ࡗࡓࠋᚑ᮶ࠊ⢾ࡢಙྕࡢᖐᒓ࡟ࡣ
TOCSYἲࢆ⏝࠸࡚࠸ࡿࡇ࡜ࡀከ࠸ࠋ
ࡋ࠿ࡋࠊᮏヨᩱ࡛ࡣΰྜ⁐፹࡛࠶ࡿࡇ࡜࡜ప ᮲௳ୗ࡛ࡢ ᐃࡢࡓࡵࠊ
⥺ᖜࡀᗈᖜ໬ࡋ࡚ಙྕࡢ㔜࡞ࡾࡀከࡃࠊᚑ᮶ࡢTOCSYἲ࡛ࡣಙྕࡢᖐᒓ
ࡀᅔ㞴࡛࠶ࡗࡓࠋࡑࡇ࡛ࠊࢫ࣌ࢡࢺ
ࣝࢆ༢⣧໬ࡍࡿࡓࡵ࡟ࠊPure shift
TOCSYἲ࡟ࡼࡗ࡚ࢹ࣮ࢱࢆྲྀᚓࡋ
ࡓࠋࡇࡢᡭἲࢆ⏝࠸ࡿࡇ࡜࡛Ỉ㓟ᇶ⏤᮶ࡢಙྕ࠿ࡽᐜ᫆࡟ࢫࢡ࣮ࣟࢫࡢ

abundanabundan

Y : parts per Million : Proton
3.97 3.95 3.93 3.91 3.89

ḟ࡟ࡇࡢ ᐃ᮲௳࡟࡚᪂ࡓ࡟ほY : parts per Million : Proton
3.97 3.95 3.93 3.91 3.89

ᛮࢃࢀࡿಙྕࡀ☜ㄆࡉࢀࡓ㸦Fig.2㸧ࠋ

6.46 6.45 6.44 6.43
X : parts per Million : Proton

10.0(thousa

6.47 6.46 6.45 6.44
X : parts per Million : Proton

6.43

10.0
(thousa

Fig. 3. Constant Time DQF-COSY and ECOSY
These spectra were collected by JNM-ECZL500R.
Constant Time DQF-COSY
x points : 6000, y points : 3000, scans : 16, NUS : 30%
ECOSY
x points : 6000, y points : 3000, scans : 24, NUS : 30%

ಙྕࡢᖐᒓࡀ࡛ࡁࡓࠋ 
J࢝ࢵࣉࣜࣥࢢ್ࢆ

ᐃࡍࡿ᪉ἲ࡜ࡋ࡚ࡣࠊH-C-O-Hࡢሙྜ
C1

ࡣConstant Time DQF-COSYἲࢆ౑⏝ࡋࡓࠋࡇࡢ᪉ἲࢆ౑⏝ࡍࡿ࡜ࠊᚑ᮶ࡢECOSYἲࡼࡾࡶࢩࣥࣉࣝ࡞ࢫ࣌ࢡࢺࣝࡀᚓࡽࢀࠊᐜ᫆࡟J ࢝ࢵࣉࣜࣥࢢ್㸦 3JHCOH 㸧ࢆồࡵࡿࡇ࡜ࡀ࡛ࡁࡓ
㸦Fig.3㸧ࠋ୍᪉ࠊC-C-O-HࡢሙྜࡣCPMG-HSQMBCἲࢆ౑⏝ࡋࠊ3JCCOHࡢࣟࣥࢢࣞࣥࢪ࢝ࢵࣉࣜࣥࢢࡢ⤖ྜᐃᩘࢆồࡵࡓࠋ
2ࡘࡢ᪉ἲ࡟ࡼࡾᚓࡽࢀࡓJ⤖ྜᐃᩘࢆ࣮࢝ࣉࣛࢫࡢᘧ࡟↷ࡽC3

H
G2OH/G2 NOEࡋྜࢃࡏࠊỈ㓟ᇶ࿘㎶ࡢ஧㠃ゅࢆᑟࡁฟࡋࡓ2ࠋィ⟬⤖ᯝ࠿ࡽ

Fig. 4. Newman projection at⪃࠼ࡽࢀࡿࢢࣝࢥࣆࣛࣀ࣮ࢫࡢ2఩ࡢNewmanᢞᙳᅗࢆFig.4࡟

2-position of Glucopyranose♧ࡍࠋᐇ㦂᮲௳ࡢ᳨ウ࡜ᵝࠎ࡞ᐃࢩ࣮ࢣࣥࢫࢆ⤌ࡳྜࢃࡏNOE correlation between protonࡿࡇ࡜࡛ࠊࡇࢀࡲ࡛ゎᯒࡀᅔ㞴࡜⪃࠼ࡽࢀ࡚ࡁࡓỈ㓟ᇶࣉࣟand hydroxyl proton at 2-positionࢺࣥࢆྵࡴ஧㠃ゅ࡟ᑐࡍࡿ▱ぢࢆNMR࡟ࡼࡾᚓࡿࡇ࡜ࡀ࡛ࡁ

of Glucopyranose was observed.

ࡓࠋ௒ᚋࠊィ⟬⛉Ꮫ࡜ࡢ⤌ࡳྜࡏ࡟ࡼࡾỈ⁐ᾮ୰ࡢศᏊࡢ❧యᵓ㐀ࡢ▱ぢࡀࡉࡽ࡟῝ࡲࡿࡇ࡜ࢆᮇᚅࡋ࡚࠸ࡿࠋ

References(1) Bruce Adams and Laura Lerner (1992)
Observation of Hydroxyl Protons of Sucrose in Aqueous Solution: No Evidence for Persistet Intramolecular
Hydrogen Bonds. J. Am. Chem. Soc. 114, 4827-4829.
(2) Hongqui Zhao, et al. (2007)
DFT and NMR Studies of 2JCOH, 3JHCOH, and 3JCCOH Spin-Couplings in Saccharides: C-O Torsional Bias and
H-Bonding in Aqueous Solution. J. Org. Chem. 72, 7071-7082.

－ 239 －

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      P46Y

VEGF165࡟ᑐࡍࡿேᕤሷᇶDsࢆྵࡴDNA࢔ࣉࢱ࣐࣮ࡢNMRゎᯒ‫ۑ‬㛗℈཭ᾏ 㸪ᰁ㇂㱟ᙪ 㸪ᆏᮏὈ୍ 
1 ༓ⴥᕤᴗ኱Ꮫ࣭⏕࿨⛉Ꮫ
2 ࢱࢢࢩࢡࢫ࣭ࣂ࢖࢜ᰴᘧ఍♫

NMR analysis of DNA aptamers containing artificial base Ds against VEGF165‫ۑ‬Tomomi Nagahama1, Tatsuhiko Someya2, Taiichi Sakamoto1
1

Chiba Institute of Technology

2

TAGCyx Biotechnologies Inc.

 Aptamers are nucleic acid molecules that show high affinity to target molecules, and these can be obtainedby the method called SELEX. The aptamers containing artificial base 7-(2-thienyl) imidazo [4,5-b] pyridine(Ds) were reported by Dr. Hirao, and are being developed as aptamer therapeutics (Xenoligo®) by TAGCyx
Biotechnologies Inc.. In this study, we performed NMR analysis of the aptamer TAGX-0001_49 that contains
Ds. The broadening of Ds signals upon binding to the target protein VEGF165 indicates that Ds is involvedin the VEGF165 binding.
࠙ᗎㄽࠚ࢔ ࣉ ࢱ ࣐ ࣮ ࡣ 㸪 Systematic Evolution of Ligands byExponential Enrichment㸦SELEX㸧ἲ࡟ࡼࡗ࡚㸪ࣛࣥࢲ࣒࡞᰾㓟ࣉ࣮ࣝࡢ୰࠿ࡽᶆⓗศᏊ࡜ࡢぶ࿴ᛶ࡟ᇶ࡙࠸࡚
㑅ᢥࡍࡿࡇ࡜࡟ࡼࡗ࡚ᚓࡽࢀࡿ᰾㓟ศᏊ࡛࠶ࡾ㸪་⸆ရࡢ᪂ࡋ࠸ࣔࢲࣜࢸ࢕ࡢࡦ࡜ࡘ࡜ࡋ࡚ᮇᚅࡉࢀ࡚࠸
ࡿ㸬࢔ࣉࢱ࣐࣮་⸆ရࡣ㸪ᢠయ་⸆ရࡢࡼ࠺࡟ᶆⓗศᏊFig. 1 Chemical structure of Ds

࡟ᑐࡋ࡚㧗࠸ぶ࿴ᛶ࡜≉␗ᛶࢆ♧ࡍࡔࡅ࡛࡞ࡃ㸪ᑠᆺ໬ࡸ໬Ꮫྜᡂࡀᐜ࡛᫆࠶ࡿ࡜࠸࠺฼Ⅼࢆࡶࡘ㸬㏆ᖺ㸪㧗ᶵ⬟࡞࢔ࣉࢱ࣐࣮ࢆ㛤Ⓨࡍࡿࡓࡵ࡟㸪ࡉࡲࡊࡲ࡞ேᕤ
ሷᇶࢆ࢔ࣉࢱ࣐࣮࡟⤌ࡳ㎸ࡴࡇ࡜ࡀヨࡳࡽࢀ࡚࠸ࡿ㸬ᖹᑿ༤ኈࡽࡣ㸪␯Ỉᛶࡢேᕤሷᇶ࡛࠶ࡿ7-㸦2-ࢳ࢚ࢽࣝ㸧࢖࣑ࢲࢰ[4, 5-b]ࣆࣜࢪࣥ㸦Ds㸧ࢆ⤌ࡳ㎸ࡴࡇ࡜࡛㸪㧗ぶ࿴ᛶࡢDNA࢔ࣉࢱ࣐࣮ࡢస〇࡟ᡂຌࡋ㸪ࡑࡢ࢔ࣉࢱ
࣐࣮ࡣኳ↛ሷᇶ࠿ࡽ࡞ࡿ᰾㓟ࣉ࣮ࣝࢆ⏝࠸ࡓSELEXἲ
࡟ࡼࡗ࡚ᚓࡽࢀࡓ࢔ࣉࢱ࣐࣮࡟ẚ࡭࡚⣙150ಸ㧗࠸⤖Fig. 2 Inhibition of VEGF165

ྜຊࢆ♧ࡍࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠸ࡿ㸦Fig. 1㸧1,2)㸬ࡇࡢ࢔

binding to VEGFR by aptamerࣉࢱ࣐࣮ࡣ㸪⾑⟶ෆ⓶ቑṪᅉᏊ㸦VEGF165㸧࡟㧗࠸≉␗ᛶ࡜ぶ࿴ᛶ࡛⤖ྜࡋ㸪VEGF165࡜ࡑࡢཷᐜయ࡜ࡢ⤖ྜࢆ㜼ᐖࡍࡿ㸦Fig. 2㸧㸬᭦࡟ࠊேᕤሷᇶ࡛
࠶ࡿDsࢆA࡟⨨᥮ࡍࡿࡇ࡜࡛㸪VEGF165࡜ࡢ⤖ྜάᛶࡀపୗࡍࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗ࡚࠸ࡿ㸬ࡑࡇ࡛ᮏ◊✲࡛ࡣ㸪Dsሷᇶࢆྵࡴ࢔ࣉࢱ࣐࣮㸦Xenoligo®㸧ࡀᶆⓗࢱࣥࣃࢡ㉁࡜㧗ぶ࿴ᛶ࡛⤖ྜ࡛ࡁࡿせᅉࡀ␯ỈᛶࡢேᕤሷᇶDs࡛࠶ࡿࡇ࡜ࢆド᫂ࡍࡿࡓࡵ࡟㸪Xenoligo®㸦TAGX-0001_49; Fig. 3㸧࡜ࡑࡢᶆⓗ࡛࠶ࡿVEGF165࡜ࡢ┦஫స⏝࡟ࡘ࠸࡚NMRἲࢆ⏝࠸࡚ゎᯒࡍࡿ㸬࢔ࣉࢱ࣐࣮㸪ேᕤሷᇶ㸪VEGF
ż࡞ࡀࡣࡲ࡜ࡶࡳ㸪ࡑࡵࡸࡓࡘࡦࡇ㸪ࡉ࠿ࡶ࡜ࡓ࠸࠸ࡕ

－ 242 －

࠙᪉ἲࠚDsࢆྵࡴTAGX-0001_49࡜ࡑࢀࢆ▷㙐໬ࡋࡓT-00221ࢆ໬Ꮫྜᡂࡋࡓ㸦Fig. 3㸧㸬ࡉࡽ࡟㸪T-00221
ࡢ3ࡘࡢࢫࢸ࣒࣮ࣝࣉ࡟┦ᙜࡍࡿ࢜ࣜࢦࢆྜᡂࡋ㸪T-00221ࡢNMRࢩࢢࢼࣝࡢᖐᒓ࡟฼⏝ࡋࡓ㸬
VEGF165࡟ࡘ࠸࡚ࡣ㸪ࡑࡢ࣊ࣃࣜࣥ⤖ྜࢻ࣓࢖ࣥ㸦VEGF_HBD㸧ࢆ㉎ධࡋ㸪TAGX-0001_49࡜ࡢ┦஫స⏝ゎᯒ࡟⏝࠸ࡓ㸬⁐፹࡜ࡋ࡚ࣜࣥ㓟⦆⾪⏕⌮㣗ሷỈ㸦PBS; 1.1 mM KH2PO4, 155 mM NaCl, 3.0
mM Na2HPO4, pH 7.4㸧ࢆ⏝࠸㸪㝈እࢁ㐣⭷ࢆ⏝࠸࡚⁐፹⨨᥮ࢆ⾜ࡗࡓ㸬600 MHzࡢNMRศගィ㸦AVANCE600㸪Bruker Biospin♫㸧ࢆ⏝࠸㸪 ࢱࣥࣃࢡ㉁Ꮡᅾୗ࣭㠀Ꮡᅾୗ୰ࡢNOESYࢫ࣌ࢡࢺࣝ
࠾ࡼࡧTOCSYࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓ㸬 ᐃ ᗘࡣ283 K࠶ࡿ࠸ࡣ298 K࡜ࡋࡓ㸬࠙⤖ᯝ࠾ࡼࡧ⪃ᐹࠚึࡵ࡟㸪TAGX-0001_49ࡢ࢖࣑ࣀࣉࣟࢺࣥࢩ
ࢢࢼࣝࢆᖐᒓࡋ㸪VEGF_HBD࡜ࡢ┦஫స⏝࡟ࡼࡿࢩࢢࢼࣝࡢኚ໬ࢆゎᯒࡋࡓ࡜ࡇࢁ㸪T31ࡢࢩࢢࢼࣝࡀᾘኻࡍࡿࡇ࡜ࡀࢃ࠿ࡗࡓ㸬ࡇࡢࡇ࡜࠿ࡽ㸪VEGF_HBD࡜ࡢ⤖ྜ࡟ࡼࡾA8:T31ࡢ
ሷᇶᑐࡀ୙Ᏻᐃ໬ࡋࡓࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬ࡉࡽ࡟㸪VEGF_HBD࡜ࡢ┦஫స⏝ࢆTOCSYࢫ࣌ࢡࢺࣝࡢࢩࢢࢼࣝኚ໬࡟ࡼࡾゎᯒࡋࡓ⤖ᯝ㸪
25␒┠ࡢDsࡀ࡯࡜ࢇ࡝ኚ໬ࡋ࡞࠸ࡢ࡟ᑐࡋ㸪34␒┠ࡢDsࡢࢩࢢࢼࣝࡀࣈ࣮ࣟࢻ࡟࡞ࡗࡓ㸬ࡇࡢࡇ࡜࠿ࡽ㸪Ds34ࡀVEGF_HBD࡜┤᥋┦஫స⏝ࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬Dsࡣ␯Ỉᛶࡀ㧗࠸ࡇ࡜࠿ࡽ㸪TAGX-0001_49ࡢVEGF࡟ᑐ

Fig. 3 Secondary structure of the aptamersࡍࡿ㠀ᖖ࡟㧗࠸ぶ࿴ᛶࡢཎᅉ࡜ࡋ࡚㸪␯Ỉⓗ࡞┦஫స⏝ࡀ㔜せ࡛࠶ࡿࡇ࡜ࡀ⪃࠼ࡽࢀࡿ㸬ࡲࡓ㸪TOCSYࢫ࣌ࢡࢺࣝ࡟࠾࠸࡚㸪CṧᇶࡢH5/H6ࡢࢡࣟࢫࣆ࣮ࢡ࡟ࡘ࠸࡚ࡶ㸪୍㒊ࡢࢩࢢࢼࣝ
ࡀVEGF_HBD࡜ࡢ┦஫స⏝࡟ࡼࡗ࡚ࣈ࣮ࣟࢻ࡟࡞ࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓ㸬ࡑࡇ࡛㸪ࢩࢢࢼࣝࡀኚ໬ࡋࡓCṧᇶࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵ㸪Ds34ࢆྵࡴ▷㙐໬ࡋࡓT-00221㸦36ṧᇶ㸧ࢆ⏝࠸࡚㸪㠀᫆ືᛶࣉࣟࢺࣥࡢࢩࢢࢼࣝࢆ㐃㙐ᖐᒓࡋࡓ㸬ࡑࡢ⤖ᯝ㸪A40࡜G44௨እࡢṧᇶࡢH8, H6, H5࠾ࡼࡧH1ƍ࡟⏤᮶ࡍࡿࢩࢢࢼࣝࢆᖐᒓࡍࡿࡇ࡜ࡀ࡛ࡁࡓ㸬ᚓࡽࢀࡓ᝟ሗࢆᇶ࡟TAGX-0001_49࡟VEGF_HBDࢆຍ࠼ࡓ㝿࡟ࣈ࣮ࣟࢻ࡟࡞ࡗࡓCṧᇶࡢH5/H6ࡢࢡࣟࢫࣆ࣮ࢡࡣ㸪C35㸪C36㸪C37⏤᮶ࡢࢩࢢࢼ࡛ࣝ
࠶ࡿࡇ࡜ࡀࢃ࠿ࡗࡓ㸬௨ୖࡢࡇ࡜࠿ࡽ㸪Ds34࠿ࡽࢫࢸ࣒Ϫࡢ㏆ഐ࡟VEGF_HBDࡀ⤖ྜࡍࡿࡇ࡜ࡀ
♧၀ࡉࢀࡓ㸬

References(1) Kimoto M. et al. (2013) Generation of high-affinity DNA aptamers using an expanded genetic alphabet.
Nature Biotechnology 31, 453-457(2) Kimoto M. et al. (2016) Post-ExSELEX stabilization of an unnatural-base DNA aptamer targeting
VEGF165 toward pharmaceutical applications. Nucleic Acids Research 44, 7487–7494－ 243 －

P47

ᅛయNMRࢆ⏝࠸ࡓ࢔࣑ࣟ࢖ࢻ࣮࣋ࢱ࢔࢖ࢯࣇ࢛࣮࣒ࡢ┦஫స⏝ࡢゎᯒ‫ۑ‬ぶἩ㑈㸪ᯇ⏣ຬ㸪⚄ཎᏕஅ㸪▼㯮㈗ஓ㸪▼஭ె㄃㸪1ᮾிᕤᴗ኱Ꮫ ⏕࿨⌮ᕤᏛ㝔
2⌮໬Ꮫ◊✲ᡤ ⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮

Analysis of amyloid-beta isoform interactions using solid-state NMR‫ۑ‬Ryo Oyadomari㸪Isamu Matsuda㸪Takayuki Kamihara㸪Takaya Ishiguro㸪and Yoshitaka Ishii
1

Department of Life Science and Technology, Tokyo Institute of Technology, Yokohama, Japan

2

Advanced NMR Development & Application Team, BDR Center, RIKEN, Yokohama, Japan
Misfolded ȕ-amyloid (Aȕ) is a peptide that is believed to prompt the onset of Alzheimer's disease (AD).

There are two main isoforms in the human brain, 40-residue Aȕ40 and 42-residue Aȕ42. Because Aȕ42 hashigher propensity to form amyloid fibril than Aȕ40 and because misfolding of Aȕ42 is widely believed totrigger AD, Aȕ42 fibrils and Aȕ40 monomers are likely to coexist in the brain at an early stage of AD. In
this study, we focused on the interaction between Aȕ40 monomer and Aȕ42 fibril and analyzed it using
solid-state NMR (SSNMR). We performed SSNMR analysis on samples obtained by incubating 13C
isotope-labeled Aȕ40 monomers with unlabeled Aȕ42 fibers. The results showed that SSNMR analysis candetect structure changes and E-sheet formation of Aȕ40 upon interaction with Aȕ42 fibrils.
࢔࣑ࣟ࢖ࢻ࣮࣋ࢱ(Aȕ)ࡣ୺࡟40–43ṧᇶࡢ࢔࣑ࣀ㓟࠿ࡽ࡞ࡿ࣌ࣉࢳࢻ࡛ࠊ⬻ෆ࡛␗ᖖจ㞟ࡋ⥺⥔໬ࡍࡿࡇ࡜࡛࢔ࣝࢶࣁ࢖࣐࣮⑓(AD)ࡢཎᅉ࡜࡞ࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿࠋ⬻ෆ࡟ࡣ୺࡟40ṧᇶࡢAȕ40࡜ࠊCᮎ➃࡟2ṧᇶࢆ㏣ຍࡋࡓ42ṧᇶࡢAȕ42ࡢ2ࡘࡢ࢔࢖ࢯࣇ࢛࣮࣒ࡀᏑᅾࡋࠊࡑࢀࡒࢀࡀ␗
ᖖจ㞟ࡋ࡚࡛ࡁࡓ࢔࣑ࣟ࢖ࢻ⥺⥔ࡢᵓ㐀ࡣ኱ࡁࡃ␗࡞ࡿࡇ࡜ࡀᅛయNMR࡟ࡼࡿゎᯒ࡛♧ࡉࢀ࡚
࠸ࡿ1,2ࠋin vitroࡢᐇ㦂࡛ࡣAȕ42ࡣAȕ40࡟ẚ࡭࡚⥺⥔໬ࡀ㏿ࡃࠊAȕ40࡛ࡣ࡞ࡃAȕ42ࡢ⬻ෆ࡛ࡢจ㞟ࡀADࡢࣜࢫࢡࣇ࢓ࢡࢱ࣮࡜఩⨨࡙ࡅࡽࢀ࡚࠸ࡿࡓࡵࠊึᮇࡢAD࡛ࡣAȕ42⥺⥔࡜Aȕ40ࣔࣀ࣐࣮ࡀ⬻ෆ࡛ඹᏑࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ
Aȕࡢࣔࣀ࣐࣮ࡀ⥺⥔ࢆᙧᡂࡍࡿ㐣⛬࡛ࡣࠊࣔࣀ࣐࣮࠿ࡽ࢜ࣜࢦ࣐࣮ࡢ≧ែࢆ⤒㐣ࡍࡿࡓࡵࠊ
⥺⥔ᙧᡂࡲ࡛࡟ᩘ᫬㛫ࡢࣛࢢࢱ࢖࣒ࡀⓎ⏕ࡍࡿࡇ࡜ࡀࠊ࢔࣑ࣟ࢖ࢻ⥺⥔࡜㑅ᢥⓗ࡟⤖ྜࡋ⺯ගࢆ
ⓎࡍࡿThioflavinT (ThT)ࢆ⏝࠸ࡓᐇ㦂࡛ሗ࿌ࡉࢀ࡚࠸ࡿࠋAȕࣔࣀ࣐࣮࡜ྠ✀ࡢAȕ⥺⥔ࡢ᩿∦(ࢩ࣮ࢻ)ࡀΰᅾࡍࡿ࡜ࡁࠊࣛࢢࢱ࢖࣒↓ࡋ࡟⥺⥔໬ࢆಁ㐍ࡍࡿࡇ࡜ࡀin vitroࡢᐇ㦂࡟ࡼࡗ࡚♧ࡉࢀ
࡚࠸ࡿ3ࠋࡋ࠿ࡋࠊSᏐ≧ࡢศᏊᵓ㐀ࢆᙧᡂࡍࡿAȕ42⥺⥔࡜Aȕ40ࣔࣀ࣐࣮ࡢඹᏑୗ࡛ࡣࠊAȕ42⥺⥔ࡣAȕ40ࣔࣀ࣐࣮ࡢ⥺⥔໬ࢆಁ㐍ࡋ࡞࠸࡜ሗ࿌ࡉࢀ࡚࠸ࡿ4,5ࠋAȕ42⥺⥔࡜Aȕ40ࡢ⥺⥔ࡢศᏊᵓ㐀ࡀ␗࡞ࡿࡇ࡜ࡀࠊ␗࡞ࡿ࢔࢖ࢯࣇ࢛࣮࣒㛫࡛ࡢࢡࣟࢫࢩ࣮ࢹ࢕ࣥࢢࡀ㉳ࡇࡽ࡞࠸ཎᅉ࡜ࡉࢀ࡚
࠸ࡿࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊAȕ40ࣔࣀ࣐࣮࡜Aȕ42⥺⥔ࡢ┦஫స⏝࡟╔┠ࡋࠊAȕ42⥺⥔࡜ΰྜࡉࢀ
ࡓAȕ40ࡢᵓ㐀ࡢኚ໬ࢆᅛయNMRࢆ⏝࠸࡚ㄪ࡭ࡓࠋ

࣮࣋ࢱ࢔࣑ࣟ࢖ࢻ
‫࠿ࡓࡋࡼ࠸ࡋ࠸ࠊࡸ࠿ࡓࢁࡄࡋ࠸ࠊࡁࡺ࠿ࡓࡽࡣࡳ࠿ࠊࡴࡉ࠸ࡔࡘࡲࠊ࠺ࡻࡾࡾࡲ࡝ࡸ࠾ۑ‬－ 244 －

Aȕ42ࢆ໬Ꮫⓗ࡟ྜᡂࡋࠊࣜࣥ㓟ࢼࢺ࣒ࣜ࢘⦆⾪ᾮ࡟⁐ゎࡉࡏAȕࣔࣀ࣐࣮⁐ᾮࢆㄪ〇ࡋࡓࠋAȕ42ࣔࣀ࣐࣮⁐ᾮࢆᐊ࡛ᅇ㌿ᨩᢾࡍࡿࡇ࡜࡛࢖࣮ࣥ࢟ࣗ࣋ࢩࣙࣥࡋࠊ⥺⥔໬ࡉࡏࡓᚋࠊ㉸㡢Ἴฎ⌮࡟ࡼࡾ᩿∦໬ࡋࡓࠋࡇࡢྠ఩యࣛ࣋ࣝࡋ࡚࠸࡞࠸Aȕ42⥺⥔᩿∦ࢆࢩ࣮ࢻ࡜ࡋ࡚13Cྠ఩యࣛ࣋ࣝࡋ
ࡓAȕ40ࣔࣀ࣐࣮⁐ᾮ࡟ຍ࠼ࠊAȕ40ࡀ⮬ᕫ㞟✚ࡍࡿ๓ࡢ཯ᛂ㛤ጞ1᫬㛫ᚋࡢࢧࣥࣉࣝࢆ㐲ᚰศ㞳࡟ࡼࡾฎ⌮ࡋ࡚ỿẊࢆᅇ཰ࡋࡓࠋࡇࡢ㐲ᚰศ㞳ࡢ᮲௳࡛ࡣ⥺⥔ࡢࡳࡀᅇ཰ࡉࢀࡿࡢ࡛ࠊࡇࡇ࡛ᅇ཰
ࡉࢀࡓAȕ40ࢧࣥࣉࣝࡣAȕ42⥺⥔᩿∦࡜┦஫స⏝ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋࡲࡓࠊAȕ40ࣔࣀ࣐࣮࡜┦஫స⏝ࡉࡏࡓࡓࡵ࡟౑⏝ࡋࡓAȕ42⥺⥔࡜ࡢᵓ㐀ࡢẚ㍑ࢆ⾜࠺ࡓࡵࠊ13Cᶆ㆑ࡋࡓAȕ42ࣔࣀ࣐࣮⁐ᾮ࡟10㸣ࡢ๭ྜ࡛Aȕ42⥺⥔ࡢࢩ࣮ࢻࢆຍ࠼ࠊ3᪥௨ୖ⤒㐣ࡋࡓࢧࣥࣉࣝࢆ㐲ᚰศ㞳࡟ࡼࡾᅇ཰ࡋ
ࡓࠋ⥺⥔໬ࡢ㐣⛬ࡣࠊThTࢆ⏝࠸࡚グ㘓ࡋࡓࠋᅇ཰ࡋࡓࢧࣥࣉࣝࡣJEOL 1 mmヨᩱ⟶࡟ワࡵࠊᅛయ
NMRࢆ⏝࠸ࡓ㸰ḟඖ 13C-13C RFDRᐃࢆ⾜ࡗࡓࠋࡲࡓᅛయNMR࡟ࡼࡿゎᯒ࡛ࡣࠊAȕ40ࣔࣀ࣐࣮ࡀAȕ40⥺⥔ࢆᙧᡂࡋࡓࡶࡢ࡜ࡣ␗࡞ࡿࢡࣟࢫࣆ࣮ࢡࡀ☜ㄆࡉࢀࡓࠋࡇࡢࡇ࡜࠿ࡽAȕ40࡜Aȕ42ࡢ㛫࡛┦஫స⏝ࡀ㉳ࡇࡾࠊᵓ㐀ኚ໬ࡋࡓࡇ࡜ࡀ♧၀ࡉࢀࡿࠋヲ⣽࡞స⏝ᶵᵓ࡟ࡘ࠸࡚ࡣࠊᙜ᪥ࡢⓎ⾲࡛㆟ㄽࢆ⾜࠺ࠋ

References(1) A. T. Petkova et al., Proc. Natl. Acad. Sci. USA, 99, 16742–16747 (2002).
(2) Y. Xiao et al., Nat. Struct. Mol. Biol., 22, 499–505 (2015).
(3) A. T. Petkova et al., Science, 307, 262–265 (2005).
(4) B. K. Yoo et al., J. Am. Chem. Soc., 140, 2781–2784 (2018).
(5)▼㯮ࡽࠊ➨58ᅇNMRウㄽ఍ࠊP60 (2019).

－ 245 －

P48Y

ศᏊ㎸ࡳྜ࠸⎔ቃୗ࡟࠾ࡅࡿDNA୕㔜㙐ᵓ㐀ࡢሷᇶᑐࡢ㛤㛢ࢲ࢖ࢼ࣑ࢡࢫࡢ⦆࿴ศᩓἲࢆ⏝࠸ࡓゎᯒ‫ۑ‬㜰ᮏ▱ᶞᒣ⨨భ኱Ọ⏣ᓫ∦ᖹṇே1ி㒔኱Ꮫ࣭࢚ࢿࣝࢠ࣮⌮ᕤᏛ◊✲ᡤ
2ி㒔኱Ꮫ࣭኱Ꮫ㝔࢚ࢿࣝࢠ࣮⛉Ꮫ◊✲⛉

Analysis of base pair opening/closing dynamics of DNA triplex structure undermolecular crowding environment using relaxation dispersion experiments‫ۑ‬Tomoki Sakamoto1,2, Yudai Yamaoki1,2, Takashi Nagata1,2, Masato Katahira1,2
1

Institute of Advanced Energy, Kyoto University

2 Graduate School of Energy Science, Kyoto University

The formation of DNA triplex structure is reportedly involved in Friedreich's ataxia. Inside the living cell is amolecular crowding environment and the behavior of DNA in such environments is thought to be different fromthat in dilute solution environments. In this study, we conducted the imino proton-water proton exchange
H[SHULPHQWDQG5 ȡUHOD[DWLRQGLVSHUVLRQH[SHULPHQWWRLQYHVWLJDWHWKHG\QDPLFVRI' 1$WULSOH[VWUXFWXUHLQ
the cell-mimicking environments reconstructed by crowding reagents, Ficoll 70 and PEG 200. The obtained
imino proton exchange rates indicated that the base pairs in triplex structure are stabilized by Ficoll 70, and aredestabilized by PEG 200. 7KH5 ȡUHOD[DWLRQGLVSHUVLRQH[SHULPHQWVXJJHVWHGWKDWWKHEDVHSDLURSHQLQJandclosing dynamics of DNA triplex structure in a molecular crowding environment is indeed different from thatin a dilute solution environment. Our study may contribute to an understanding of the stability and dynamics of
triplex structure in the molecular crowding environment such as inside the living cells.
DNAࡢᙧᡂࡍࡿ୕㔜㙐ᵓ㐀ࡣࠊࡀࢇ࡟㛵㐃ࡍࡿ㑇ఏᏊࡢ㌿෗ࡸࣇ࣮ࣜࢻࣛ࢖ࣄ㐠ືኻㄪ⑕ࡢⓎ⑕࣓࢝ࢽࢬ࣒࡟㛵୚ࡍࡿࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠾ࡾࠊDNA୕㔜㙐ᵓ㐀ࢆᶆⓗ࡜ࡋࡓ๰⸆ࡀᮇᚅࡉࢀ࡚
࠸ࡿࠋ㑇ఏᏊⓎ⌧ไᚚ࡟࠾࠸࡚ࡣࠊDNA஧㔜㙐ᵓ㐀ࡢሷᇶᑐࡢ㛤㛢ࢲ࢖ࢼ࣑ࢡࢫࡀ㔜せ࡞ᙺ๭ࢆᯝࡓࡍࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠾ࡾࠊࡑࡢࢱ࢖࣒ࢫࢣ࣮ࣝࡣ࣑ࣜ⛊࠿ࡽ࣐࢖ࢡࣟ⛊࡛࠶ࡿࠋ⣽⬊ෆࡣศᏊ㎸ࡳྜ࠸⎔ቃ࡛࠶ࡿࠋࡇࡢࡼ࠺࡟ᕼⷧ⁐ᾮ࡜ࡣ≀⌮໬Ꮫⓗ᮲௳ࡢ␗࡞ࡿ⮬↛⎔ቃࡀDNA୕㔜㙐ᵓ㐀࡟୚࠼ࡿᙳ㡪ࢆㄪ࡭ࡿࡓࡵ࡟ࠊ✀ࠎࡢぶỈᛶ㧗ศᏊࢆศᏊ
㎸ࡳྜ࠸ヨ⸆(ࢡࣛ࢘ࢲ࣮)࡜ࡋ࡚฼⏝ࡋࡓ⣽⬊ෆ⎔ቃᶍೌ Fig. 1. The sequence and secondary⣔ࡀ฼⏝ࡉࢀ࡚࠸ࡿࠋUVࡸCDࢆ⏝࠸ࡓゎᯒ࡟ࡼࡾࠊ⣽⬊ structure of PT-ODN.
ෆ⎔ቃᶍೌ⣔࡟࠾࠸࡚ࡣDNA୕㔜㙐ᵓ㐀ࡢ⇕Ᏻᐃᛶࡀᕼⷧ⁐ᾮ⎔ቃୗ࡜ࡣ␗࡞ࡿࡇ࡜ࡀሗ࿌ࡉࢀ
࡚࠸ࡿ1ࠋࡋ࠿ࡋࠊࡇࢀࡽࡢゎᯒ࠿ࡽࡣሷᇶᑐศゎ⬟࡛ࡢᏳᐃᛶࡸ࣑ࣜ⛊࠿ࡽ࣐࢖ࢡࣟ⛊ࡢᵓ㐀ࢲ࢖ࢼ࣑ࢡࢫ࡟୚࠼ࡿᙳ㡪࡟ࡘ࠸࡚ࡣ᝟ሗࡀᚓࡽࢀ࡚࠸࡞࠸ࠋᮏ◊✲࡛ࡣࠊNMRࢆ⏝࠸࡚ࠊ⣽⬊ෆ⎔ቃᶍೌ⣔࡟࠾ࡅࡿDNA୕㔜㙐ᵓ㐀ࡢሷᇶᑐศゎ⬟ࡢᏳᐃᛶཬࡧ࣑ࣜ⛊࠿ࡽ࣐࢖ࢡࣟ⛊ࡢᵓ㐀ࢲ࢖ࢼ࣑ࢡࢫࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜࡛ࠊ⣽⬊ෆࡢศᏊ㎸ࡳྜ࠸⎔ቃࡀDNA୕㔜㙐ᵓ㐀࡟୚࠼ࡿᙳ
㡪࡟㛵ࡍࡿ▱ぢࢆᚓࡿࡇ࡜ࢆ┠ⓗ࡜ࡋࡓࠋ᰾㓟㸪ศᏊ㎸ࡳྜ࠸⎔ቃ⦆࿴ศᩓἲ
‫ࡁࡶ࡜࡜ࡶ࠿ࡉۑ‬㸪ࡸࡲ࠾ࡁࡺ࠺ࡔ࠸࡞ࡀࡓࡓ࠿ࡋ࠿ࡓࡦࡽࡲࡉ࡜

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ᮏ◊✲࡛ࡣࠊin vitroཬࡧ⣽⬊ෆ2࡛ᖹ⾜ᆺࡢDNA୕㔜㙐ᵓ㐀ࢆᙧᡂࡍࡿࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠸ࡿ
࢜ࣜࢦDNA(PT-ODN) (Fig. 1)ࢆ⏝࠸ࡓࠋ⣽⬊ෆ⎔ቃᶍೌ⣔ࡢᵓ⠏࡟ࡣࢡࣛ࢘ࢲ̿࡜ࡋ୍࡚⯡ⓗ࡟⏝࠸ࡽࢀࡿFicoll 70 ࠾ࡼࡧPEG 200ࢆ⏝࠸ࡓࠋྛNMR ᐃ࡟࠾࠸࡚ࡣࠊ᰾㓟ࡢሷᇶᑐࡢ≧ែࢆᩄឤ࡟཯ᫎࡍࡿ࢖࣑ࣀࣉࣟࢺࣥ㡿ᇦ࡟ὀ┠ࡋࡓࠋࡲࡎࠊࢡࣛ࢘ࢲ̿ࡀDNA୕㔜㙐ᵓ㐀࡟ཬࡰࡍᙳ㡪ࢆㄪ࡭ࡿࡓࡵ࡟ࠊ15 v/v%ࢡࣛ࢘ࢲ࣮Ꮡᅾୗ࠾
ࡼࡧ㠀Ꮡᅾୗ࡟࠾ࡅࡿPT-ODNࡢ1D 1H NMRࢫ࣌ࢡࢺࣝࢆẚ㍑ࡋࡓࠋ࠸ࡎࢀࡢ᮲௳ୗ࡟࠾࠸࡚ࡶ
ᵓ㐀ࡢᮎ➃㒊ศ࡟ᑐᛂࡍࡿࢩࢢࢼࣝࢆ㝖࠸࡚ࢫ࣌ࢡࢺࣝࣃࢱ࣮ࣥࡀࡼࡃ୍⮴ࡋ࡚࠸ࡿࡇ࡜࠿ࡽࠊ
Ficoll 70ࡲࡓࡣPEG 200Ꮡᅾ᮲௳ୗ࡟࠾࠸࡚ࡶࠊࢡࣛ࢘ࢲ࣮㠀Ꮡᅾ᮲௳ୗ࡜ࡼࡃఝࡓᖹ⾜ᆺ୕㔜㙐ᵓ㐀(Fig. 1)ࡀᙧᡂࡉࢀ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡗࡓࠋ
ḟ࡟ࠊDNA୕㔜㙐ᵓ㐀ࡢྛሷᇶᑐࡢᏳᐃᛶࢆホ౯ࡍࡿࡓࡵ࡟ࠊ
࢖࣑ࣀࣉࣟࢺࣥ࡜⁐፹ࡢỈࣉࣟࢺࣥ࡜ࡢ஺᥮㏿ᗘ(k1H)ࡢゎᯒࢆ⾜ࡗࡓࠋ㛢ࡌࡓሷᇶᑐ୰࡛Ỉ⣲⤖ྜࢆᙧᡂࡋ࡚࠸ࡿ࢖࣑ࣀࣉࣟࢺࣥࡣỈ࡜ࡢ஺᥮ࡀᢚ࠼ࡽࢀ࡚࠸ࡿࡀࠊሷᇶᑐࡀ㛤࠸ࡓ≧ែ࠿ࡽࡣᐜ᫆࡟Ỉ࡜ࡢ஺᥮ࡀ⏕ࡌࡿࠋࡑࡢࡓࡵࠊk1HࡣሷᇶᑐࡢᏳᐃᛶࢆ཯ᫎࡍࡿࠋ
Ficoll 70ཬࡧPEG 200Ꮡᅾୗ࡟࠾ࡅࡿk1Hࢆᚓࡿࡇ࡜࡟ᡂຌࡋࡓ(Fig.
2)ࠋ࡯ࡰ඲࡚ࡢሷᇶᑐ࡟ࡘ࠸࡚ࠊࢡࣛ࢘ࢲ࣮㠀Ꮡᅾୗ࡟ẚ࡭࡚
Ficoll 70Ꮡᅾୗ࡛ࡣࠊk1HࡀῶᑡࡋࠊPEG 200Ꮡᅾୗ࡛ࡣk1Hࡀቑຍࡋࡓࠋࡇࡢࡇ࡜࠿ࡽࠊᖹ⾜ᆺDNA୕㔜㙐ᵓ㐀ࡢከࡃࡢሷᇶᑐࡣࠊࢡ
ࣛ࢘ࢲ࣮㠀Ꮡᅾ᮲௳ୗ࡟ẚ࡭࡚Ficoll 70ࡢῧຍ࡟ࡼࡗ࡚Ᏻᐃ໬ࡋࠊ
PEG 200ࡢῧຍ࡟ࡼࡗ࡚୙Ᏻᐃ໬ࡍࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡇࡢഴྥ
ࡣUVࢆ⏝࠸ࡓኚᛶ ᗘ(Tm)ゎᯒࡢഴྥ࡜ࡶ୍⮴ࡋࡓࠋࡇࢀࡽࡢ⤖ Fig. 2. The representativeᯝࡣ௨ୗࡢࡼ࠺࡟⪃࠼ࡽࢀࡿ㸸(1) ぶỈᛶ㧗ศᏊ࡛࠶ࡿFicoll 70ࡣ k1H values for PT-ODN in
the absence and presence of᤼㝖య✚ຠᯝࢆቑᙉࡋࠊࡑࡢ⤖ᯝ୕㔜㙐ᵓ㐀ࡀᏳᐃ໬ࡍࡿࠋ(2)either 15 v/v% Ficoll 70 orぶỈᛶపศᏊ࡛࠶ࡿPEG 200ࡣDNA࡟㏆᥋ࡋࠊDNAࡢỈ࿴Ẇ࡟ᙳ PEG 200.
㡪ࢆཬࡰࡍࡇ࡜࡛୕㔜㙐ᵓ㐀ࢆ୙Ᏻᐃ໬ࡍࡿࠋ
ḟ࡟ࠊࢡࣛ࢘ࢲ̿Ꮡᅾୗ࡟࠾ࡅࡿDNA୕㔜㙐ᵓ㐀ࡢ࣑ࣜ⛊࠿ࡽ࣐࢖ࢡࣟ⛊ࡢᵓ㐀ࢲ࢖ࢼ࣑ࢡ
ࢫࠊ༶ࡕሷᇶᑐࡢ㛤㛢㢖ᗘ࡟㛵ࡍࡿ᝟ሗࢆᚓࡿࡓࡵ࡟ࠊ1D 1H R1Ȩ⦆࿴ศᩓᐃࢆ⾜࠸ࠊᵓ㐀ኚ

໬ࡢ㏿ᗘᐃᩘkex (= kopen + kclose)ࢆồࡵࡓࠋࡇࡇ࡛ࠊkopenࡣሷᇶᑐࡀ㛤ࡃ㝿ࡢࠊkcloseࡣሷᇶᑐࡀ㛢ࡌࡿ㝿ࡢ㏿ᗘᐃᩘࢆ⾲ࡋ࡚࠸ࡿࠋࢡࣛ࢘ࢲ࣮㠀Ꮡᅾ᮲௳ୗ࠾ࡼࡧFicoll 70ࡲࡓࡣPEG 200Ꮡᅾୗ࡟࠾࠸࡚ࠊPT-ODNࡢᖹ⾜ᆺDNA୕㔜㙐ᵓ㐀ࡢkex್ࢆᚓࡿࡇ࡜࡟ᡂຌࡋࡓࠋࡇࡢ⤖ᯝࠊFicoll 70ཬ
ࡧPEG 200Ꮡᅾ᮲௳ୗ࡟࠾࠸࡚ࡣࠊࢡࣛ࢘ࢲ̿㠀Ꮡᅾୗ࡜ẚ㍑ࡋ࡚kex್ࡀ␗࡞ࡿࡇ࡜ࡀศ࠿ࡗ
ࡓࠋࡇࡢ⤖ᯝࡣࠊFicoll 70ཬࡧPEG 200Ꮡᅾ᮲௳ୗ࡟࠾࠸࡚ࡣࠊᖹ⾜ᆺDNA୕㔜㙐ᵓ㐀ࡢሷᇶᑐࡢ㛤㛢ࢲ࢖ࢼ࣑ࢡࢫࡀࢡࣛ࢘ࢲ̿㠀Ꮡᅾୗ࡜ࡣ␗࡞ࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋ
ᮏ◊✲࡛ࡣศᏊ㎸ࡳྜ࠸⎔ቃୗ࡟࠾ࡅࡿDNA୕㔜㙐ᵓ㐀ࡢሷᇶᑐศゎ⬟࡛ࡢᏳᐃᛶࠊࢲ࢖ࢼ࣑
ࢡࢫࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵ࡟ࢡࣛ࢘ࢲ̿ࢆ฼⏝ࡋࡓ⣽⬊ෆ⎔ቃᶍೌ⣔ࢆ⏝࠸࡚✀ࠎࡢNMR ᐃࢆ⾜ࡗࡓࠋࢡࣛ࢘ࢲ̿ࡢῧຍࡣࠊDNA୕㔜㙐ࡢᵓ㐀ࡑࡢࡶࡢ࡟ࡣ኱ࡁ࡞ᙳ㡪ࡣ୚࠼࡞࠸୍᪉࡛ሷᇶ
ᑐࡢᏳᐃᛶ࠾ࡼࡧࡑࡢ㛤㛢㢖ᗘ࡟ᙳ㡪ࢆ୚࠼ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡇࢀࡽࡢ⤖ᯝࡣ⣽⬊ෆࡢศᏊ㎸ࡳྜ࠸⎔ቃࡀDNA୕㔜㙐ᵓ㐀࡟୚࠼ࡿᙳ㡪࡟ࡘ࠸࡚⌮ゎࡍࡿࡇ࡜࡟ᙺ❧ࡘ࡜ᮇᚅࡉࢀࡿࠋ
References(1) S. Nakano, D. Miyoshi, N. Sugimoto, Chem. Rev., 114, 2733-2758, 2014
(2) T. Sakamoto, Y. Yudai, T. Nagata, M. Katahira, Chem. Commun., 57, 6364-6367, 2021

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P49

In-cell NMR࡟ࡼࡿlinear diubiquitinࡢin-situ❧యᵓ㐀ゎᯒ‫ۑ‬ᒇ㒊⚈኱㸪⏣ᓊு㤿㸪㬞ᚿ⏣୍㸪⨾ᕝ ົ㸰㸪⊦⫤᫭௓㸪ụ㇂㕲ර㸪ఀ⸨ 㝯
1ᮾி㒔❧኱Ꮫ࣭኱Ꮫ㝔⌮Ꮫ◊✲⛉

2⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮In-situ structure determination of linear diubiquitin by in-cell NMR spectroscopy‫ۑ‬Yoshihiro Yabu1, Ryoma Tagishi1, Hajime Kamoshida1, Tsutomu Mikawa2, Kousuke Inomata1,
Teppei Ikeya1, and Yutaka Ito1
1

Department of Chemistry, Tokyo Metropolitan University

2

RIKEN Center for Biosystems Dynamics ResearchLinear polyubiquitin, in which the carboxyl group of a ubiquitin monomer (Ub) is covalently bound to theD-amino group of another Ub, contributes specifically to the regulation of the NF-kB pathway that is crucial
for inflammation and immune regulation [1]. The 3D structure and dynamics of linear-polyubiquitin may be
important for the regulation of a wide range of NF-kB signalling. X-ray crystallography of linear-diUb, inwhich two Ub domains are connected between the C- and N-terminus, has demonstrated two different states:
closed and opened forms upon relative distances of two Ub domains [2,3,4]. On the other hand, FRET, SAXS,
and MD analyses of linear-diUb in solution have reported a semi-close state that is different from the closed
and opened states in crystal [5,6], and solution NMR suggested that linear-diUb is in a conformational
equilibrium between the open and semi-close forms. In this study, we show the 3D structure of linear-diUb
in situ by applying in-cell NMR techniques with PREs and PCSs and multi-state structure calculation.
䛆ᗎㄽ䛇㻌 䝠䝖linear diubiquitin䠄linear-diUb䠅䛿䠈ubiquitin⺮ⓑ㉁䠄Ub䠈76䜰䝭䝜㓟ṧᇶ䠅䛜┤㙐≧䛻2ศᏊ㐃䛺䛳䛯ᵓ㐀䜢ᣢ䛱,䝬䝹䝏䝗䝯䜲䞁⺮ⓑ㉁䛸䛸䜙䛘䜛䛣䛸䛜䛷䛝䜛䠊Ub䛜┤㙐≧䛻」ᩘಶ㐃䛺䛳䛯
linear polyubiquitin䛿䠈⅖⑕䜔ච␿ไᚚ䛻㔜せ䛺NF-kB⤒㊰䛾ไᚚ䛻≉␗ⓗ䛻ᐤ୚䛧䛶䛔䜛䛣䛸䛜᫂䜙䛛䛻䛺䛳䛶䛔䜛[1]䠊ᗈ⠊䛺NF-kB䝅䜾䝘䝹ไᚚ䛻㛵䜟䜛linear polyUb䛾ศᏊㄆ㆑ᶵᵓ䛻䛿䠈
linear polyUb䛾❧యᵓ㐀䜔䝎䜲䝘䝭䜽䝇䛜ᐤ୚䛧䛶䛔䜛䛸⪃䛘䜙䜜䛶䛔䜛䠊䛧䛛䛧䠈linear-diUb䛾X⥺⤖ᬗᵓ㐀ゎᯒ䛛䜙䛿䠈Ub䝗䝯䜲䞁䛜㏆᥋䛧䛯closeᆺ䛸㞳䜜䛯openᆺ䛾2≧ែ䛜[2,3,4]䠈⁐ᾮ୰䛻䛚䛡䜛
FRET䜔SAXS䠈MD䜢⏝䛔䛯ゎᯒ䛷䛿䠈⤖ᬗᵓ㐀䛸䛿␗䛺䜛semi-closeᆺ䛜ሗ࿌䛥䜜䛶䛔䜛[5,6]䠊䜎
䛯䠈ᕼⷧ⁐ᾮୗ䛷䛾NMRゎᯒ䛷䛿䠈openᆺ䛸semi-closeᆺ䛾䝁䞁䝣䜷䝯䞊䝅䝵䞁ᖹ⾮䛜♧၀䛥䜜䛯䠊୍᪉䛷䠈⣽⬊ෆ䛻䛚䛡䜛䝬䝹䝏䝗䝯䜲䞁⺮ⓑ㉁䛾䝗䝯䜲䞁㓄ྥᵓ㐀䜔䠈䛭䛾䝎䜲䝘䝭䜽䝇䜢ཎᏊศゎ⬟䛷ゎᯒ䛧䛯౛䛿䜋䛸䜣䛹ሗ࿌䛥䜜䛶䛔䛺䛔䠊䛭䛣䛷ᮏ◊✲䛷䛿䠈in-cell NMRゎᯒ䛛䜙䠈⣽⬊ෆ⎔ቃ䛷䛾
linear-diUb䛾䝗䝯䜲䞁㛫┦ᑐ㓄⨨䜢Ỵᐃ䛧䠈ᕼⷧ⁐ᾮ୰䛸⣽⬊ෆ⎔ቃୗ䛷䛾䝗䝯䜲䞁㓄ྥ䛾ᕪ␗䜢᫂䜙䛛䛻䛩䜛䛣䛸䜢┠ᶆ䛸䛧䛯䠊⣽⬊ෆ䝗䝯䜲䞁㛫┦ᑐ㓄⨨䛾Ỵᐃ䛻䛿䠈୺䛻Pseudo-contact Shift (PCS)䛸
Paramagnetic Relxation Enhancement (PRE)䜢ᵓ㐀᝟ሗ䛸䛧䛶⏝䛔䠈」ᩘ䝁䞁䝣䜷䝯䞊䝅䝵䞁䜢௬ᐃ䛧䛯multi-state❧యᵓ㐀ィ⟬䜢᥇⏝䛩䜛䛣䛸䛻䛧䛯䠊In-cell NMR㸪ᖖ☢ᛶNMR㸪⺮ⓑ㉁ࡢ❧యᵓ㐀䕿䜔䜆䜘䛧䜂䜝䠈䛯䛞䛧䜚䜗䛖䜎䠈䛛䜒䛧䛰䛿䛨䜑䠈䜏䛛䜟䛴䛸䜐䠈䛔䛾䜎䛯䛣䛖䛩䛡䠈䛔䛡䜔䛶䛳䜊䛔䠈䛔䛸䛖䜖䛯䛛

－ 248 －

䛆ᐇ㦂䛇䛇㻌 ᖖ☢ᛶ㔠ᒓ䝍䜾䛸䛾⤖ྜ䛾䛯䜑䛻Cysṧᇶ䜢᪂䛯䛻ᑟධ䛧䛯linear-diUb(S133C)䜢ㄪ〇䛧䛯䠊኱⭠⳦ෆⓎ⌧⣔䜢⏝䛔䛶ㄪ〇䛧䛯 15Nᶆ㆑
య䜢䠈SLOἲ䛻䜘䜚䝠䝖ᇵ㣴⣽⬊HeLa䛻ᑟධ䛧䠈
2D 1H-15N SOFAST-HMQC䝇䝨䜽䝖䝹䜢 ᐃ䛩䜛䛣䛸䛷䠈in-cell NMRゎᯒ䛾䛯䜑䛾᮲௳᳨ウ䜢⾜䛳䛯䠊ḟ䛻䠈ᖖ☢ᛶ㔠ᒓ⤖ྜ䝍䜾䛾ᖖ☢ᛶຠᯝ 䛾 ᙉ䛥 䛾 ホ౯ 䛸 䠈཯ ᛂᛶ 䛾 ᳨ウ 䛾 䛯䜑 䛻 䠈
DO3MA-3BrPy 䛸4PhSO2-PyMTA䜢䛭䜜䛮䜜linear-diUb䛸཯ᛂ䛥䛫䛶ᛶ⬟䜢ẚ㍑䛧䛯䠊
䛆⤖ᯝ䛸⪃ᐹ䛇䛇㻌 In-cell NMRᐇ㦂䛻䛴䛔䛶䛿䠈㟁Fig.1 1H-15N SOFAST-HMQC spectrum of 15Nlabelled linear-diUb in HeLa cells.

Ẽ✸Ꮝἲ䛻䜘䜛䝠䝖ᇵ㣴⣽⬊䠄HeLa⣽⬊䠅䜈䛾linear-diUb

(a)

(b)

䛾ᑟධ䛻ᡂຌ䛧䠈⣽⬊ෆ⎔ቃ䛷䛾linear-diUb䝇䝨䜽䝖䝹䛾㧗ឤᗘほ䛻ึ䜑䛶ᡂຌ䛧䛯(FFig.1)䠊䛣䛾in-cell NMR䝇䝨䜽䝖䝹䜢ᕼⷧ⁐ᾮ୰䛷䛾䝇䝨䜽䝖䝹䛸ẚ㍑䛩䜛䛸䠈ᕼⷧ⁐ᾮ୰䛸䛿␗䛺䜛᪂䛯䛺䝢䞊䜽䜔䝢䞊䜽䛾䝅䝣䝖ኚ໬䛜୺䛻6䛴䛾䜰䝭䝜㓟䠄K6䠈A46䠈H68䠈K82䠈A122䠈H144䠅䛷ほ䛥䜜䛯(FFig.2)䠊䛭䜜䜙䛾ኚ໬䛾୍㒊䛜Ub䛾┦஫స⏝㒊఩䛸䛧䛶▱䜙䜜䜛㡿ᇦ䛻Ꮡᅾ䛩䜛ṧᇶ䛸୍⮴䛧䛶䛔䛯䛣䛸䛛䜙䠈linear-(c)

diUb䛿⣽⬊ෆ䛷Ub⤖ྜ⺮ⓑ㉁䛸≉␗ⓗ┦஫స⏝䛧䛶䛔䜛䛣䛸䛜♧၀䛥䜜䛯䠊ᖖ☢ᛶ㔠ᒓ⤖ྜ䝍䜾䛾᳨ウ䛾⤖ᯝ䠈཯ᛂᛶ䛾㧗䛟䠈ᙉ䛔
PCS್䛾ᚓ䜙䜜䛯4PhSO2-PyMTA䛜䠈in vitro䛸in-cell䛾ゎᯒ䛻㐺䛧䛶䛔䜛䛸ุ᩿䛧䛯䠊⌧ᅾ䛿4PhSO2-PyMTA䜢⏝䛔䛶Ln3+䜢ᑟධ䛧䛯ヨᩱ䜢⏝䛔䛶䠈⣽⬊ෆPCS䛸PRE䜢ྲྀᚓ䛩䜛ᐇ㦂䜢㐍䜑䛶䛔䜛䠊ᚓ䜙䜜䛯PCS䛚䜘䜃PRE᝟ሗ䛛䜙䠈⣽⬊ෆ⎔ቃ䛷䛾䝗䝯䜲䞁㛫┦ᑐ㓄⨨䛾Ỵᐃ䜢┠ᣦ䛩䠊䛥
䜙䛻䠈PCS䛚䜘䜃PRE᝟ሗ䜢⏝䛔䛯multi-state❧యᵓ㐀ィ⟬ἲ䛻䜘䜚䠈⁐ᾮ୰䛚䜘䜃⣽⬊ෆ䛷䛾䝗䝯䜲䞁㛫┦ᑐ㓄⨨䛾ከᵝ䛺ᵓ㐀䜢ྍど໬䛩䜛䠊䛣䜜䛻䜘䜚䠈⏕⌮ⓗ᮲௳ୗ䛻䜘䜚Fig.2 (a) and (b), some 1H-15N correlation
peaks exhibiting apparent chemical shiftdifferences between in vitro (black) andin cells (grey). (c), residues showing
distinct chemical shift changes (black)mapped onto a ribbon model of thecrystal structure of linear diUb (2W9N).

㏆䛔⎔ቃ䛷䛾linear-diUb䛾ᵓ㐀䛸䝎䜲䝘䝭䜽䝇䜢᫂䜙䛛䛻䛧䠈⣽⬊ෆ䛷䛾䛭䛾ศᏊᶵᵓ䜢ゎ᫂䛩䜛䛣䛸䜢┠ᣦ䛩䠊ࠚ࠙ཧ⪃ᩥ⊩ࠚ
[1] Tokunaga, F., J. Biochem. 154, 313-323 (2013); [2] Rohaim, A. et al., Acta. Crystallogr. D. Biol. Crystallogr.
68, 102-108 (2012); [3] Thach, T.T. et al., Acta. Crystallogr. D. Biol. Crystallogr. 72, 524-535 (2016); [4]Komander, D. et al., EMBO. Rep. 10, 466-473 (2009); [5] Ye, Y. et al., Nature 492, 266-270 (2012); [6] Jussupow,
A. et al., Sci. Adv. 6, eabc3786 (2020).

－ 249 －

P50Y

໬Ꮫࢩࣇࢺ࠿ࡽ᥎ᐃࡍࡿ࣊ࣜࢵࢡࢫᙧᡂ๭ྜ
‫ۑ‬ᰗ⏣ౡᶞ㸪ྜྷ⏣Ύ⨾ ⸨ཎ࿴ኵ㸪ụཱྀ㞞㐨1๰౯኱Ꮫ኱Ꮫ㝔 ⌮ᕤᏛ◊✲⛉ ⏕࿨⌮Ꮫᑓᨷ

2๰౯኱Ꮫ኱Ꮫ㝔 ᕤᏛ◊✲⛉ ⏕࿨᝟ሗᕤᏛᑓᨷ

Helical structure populations estimated from chemical shifts‫ۑ‬Yuuki Yanagida1, Kiyomi Yoshida1, Kazuo Fujiwara1, Masamichi Ikeguchi1
1

Department of Biosciences, Graduate School of Science and Engineering, Soka University

2

Department of Bioinformatics, Graduate School of Engineering, Soka University

CHIBLǻF is a fragment of ȕ-lactoglobulin corresponding to the residues 97-142. It has a disulfide bond(Cys106-Cys119) and forms Į-helices in 98-107 and 114-135 regions. It has been shown that the helices aredestabilized when the disulfide bond is cleaved. From this result, we assumed that the loop formation by adisulfide bond reduces the number of conformations that can be taken by the peptide chain in the loop andfacilitates the nucleation of the Į-helix. To confirm this hypothesis, we constructed three derivatives of
CHIBLǻF in which one, three, seven Gly residue(s) was(were) inserted between the residue 109 and110. We
calculated the fractional populations of Į-helices formed in these model peptides from secondary chemical
shifts. The results showed that the fractional populations decreased with increasing the number of inserted
residues and supported our hypothesis.
Introduction࣐࢘ȕ-ࣛࢡࢺࢢࣟࣈࣜࣥࡣ㓟ᛶpH, ሷ㠀Ꮡᅾୗ࡟࠾࠸࡚ࠊ஧ḟᵓ㐀ࢆᣢࡕ࡞ࡀࡽࠊ୕ḟᵓ㐀ࡢᔂቯࡋࡓ୰㛫ⓗ࡞ኚᛶ≧ែࢆᙧᡂࡍ

114

ࡿࠋࡑࡢ୰㛫≧ែ࡟࠾࠸࡚ࠊ㠀ኳ↛ࡢĮ࣊ࣜࢵࢡࢫࢆᙧᡂࡋ࡚࠸ࡿ
㡿ᇦࢆCHIBL (core of the helical intermediate of ȕ-lactoglobulin) ࡜ྡ࡙ࡅࡓ[1]ࠋCHIBLࡼࡾF-strand㡿ᇦࢆḞኻࡉࡏࡓCHIBLǻFࡣࠊࢪࢫࣝࣇ࢕ࢻ⤖ྜ (Cys106-Cys119)ࢆᣢࡕࠊ98-107࡜114-135㡿ᇦ࡟Į࣊

97ࣜࢵࢡࢫࢆᙧᡂࡋ࡚࠸ࡿࡇ࡜ࡀ♧ࡉࢀࡓ[2]ࠋࡲࡓࠊࡇࢀࡲ࡛࡟ࠊ
1)ࢪࢫࣝࣇ࢕ࢻ⤖ྜࡀษ᩿ࡉࢀࡿ࡜࣊ࣜࢵࢡࢫྵ㔞ࡀῶᑡࡍࡿࡇ
࡜ࠊ2)97-110㡿ᇦ࡜111-138㡿ᇦ࡟ᑐᛂࡍࡿ▷࠸࣌ࣉࢳࢻ᩿∦ࡣ࠸ࡎࢀࡶ࣊ࣜࢵࢡࢫࢆᙧᡂࡋ࡞࠸ࡇ࡜ࠊ3)ࡇࡢ2ࡘࡢ᩿∦ࢆࢪࢫࣝࣇ࢕

142
Fig.1 CHIBLǻF

ࢻ⤖ྜ࡛㐃⤖ࡋ࡚ࡶ࣊ࣜࢵࢡࢫࡣᙧᡂࡉࢀ࡞࠸ࡇ࡜ࡀ♧ࡉࢀ࡚࠸ࡿ
[2]ࠋࡇࢀࡽࡢ⤖ᯝ࠿ࡽࠊࢪࢫࣝࣇ࢕ࢻ⤖ྜ࡟ࡼࡗ࡚࣮ࣝࣉࡀᙧᡂࡉࢀࡿ࡜ࠊ࣮ࣝࣉෆࡢ࣌ࣉࢳࢻ
㙐ࡀྲྀࡾ࠺ࡿࢥࣥࣇ࢛࣮࣓࣮ࢩࣙࣥᩘࡀῶࡾࠊ࣊ࣜࢵࢡࢫࡢ᰾ᙧᡂࡀಁ㐍ࡉࢀࡿ࡜⪃࠼ࡓࠋࡇࡢ௬ㄝࢆ☜࠿ࡵࡿࡓࡵ࡟ࠊCHIBLǻF (ࡇࡇ࡛ࡣG0࡜࿧ࡪ)ࡢṧᇶ109࡜110ࡢ㛫࡟ࡑࢀࡒࢀ1ࡘࠊ3ࡘࠊ7ࡘࡢGlyṧᇶࢆᤄධࡋࡓ3ࡘࡢኚ␗య (G1ࠊG3ࠊG7)ࢆస〇ࡋࠊ෇஧Ⰽᛶ(CD)ࢫ࣌ࢡࢺ
ࣝࢆ ᐃࡋࡓࠋNMRࡢ⤖ᯝ࠿ࡽ஧ḟ໬Ꮫࢩࣇࢺࢆ⟬ฟࠊࣇ࢛࣮ࣝࢹ࢕ࣥࢢ୰㛫యࡢࣔࢹࣝ࣌ࣉ
ࢳࢻ࡟ᙧᡂࡉࢀࡿĮ࣊ࣜࢵࢡࢫࡢᙧᡂ๭ྜࢆ࠸ࡃࡘ࠿ࡢ໬Ꮫࢩࣇࢺ࠿ࡽ᥎ᐃࡍࡿ᪉ἲ࡛ィ⟬ࡋࠊẚ㍑ࢆ⾜ࡗࡓࠋ
Į࣊ࣜࢵࢡࢫ㸪஧ḟ໬Ꮫࢩࣇࢺ, ࢪࢫࣝࣇ࢕ࢻ⤖ྜ‫ࡁ࠺ࡺࡔࡂ࡞ࡸۑ‬㸪ࡼࡋࡔࡁࡼࡳ, ࡩࡌࢃࡽ࠿ࡎ࠾, ࠸ࡅࡄࡕࡲࡉࡳࡕ

－ 250 －

Methods
G0, G1, G3, G7࡟ࡘ࠸࡚190-250 nmࡢCDࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓࠋࡲࡓ222 nm࡛⇕㌿⛣ࢆ ᐃࡋࡓࠋࡲࡓᏳᐃྠ఩యᶆ㆑ࢆࡋࡓࢧࣥࣉ࡛ࣝNMR ᐃࢆ12Υ࡛⾜ࡗࡓࠋ୺㙐ࡢ࢔ࢧ࢖࣓ࣥࢺࢆࡍࡿ
ࡓࡵ࡟1H-15N HSQC, HNCO, HN(CA)CO, CBCA(CO)NH, HNCACB, HBHA(CO)NH, HBHANHࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓࠋ1ḟࢩࣇࢺ࡟6ṧᇶࡢ┤㙐≧࣌ࣉࢳࢻࡢ໬Ꮫࢩࣇࢺ[3]ࢆ⏝࠸࡚ࠊ1HĮࠊ13Cȕࠊ13CĮࠊ
13COࡢ2ḟࢩࣇࢺࢆ⟬ฟࡋࡓࠋࡲࡓࠊ1HĮࠊ13Cȕࠊ13CĮࠊ13COࠊNࠊHNࡢ໬Ꮫࢩࣇࢺࢆ࠿ࡽࠊį2D[4]ࠊ

ncSCP[5]ࢆ⏝࠸࡚஧ḟᵓ㐀ࡢᙧᡂ๭ྜࢆ⟬ฟࡋࡓࠋResults and DiscussionCDࢫ࣌ࢡࢺࣝࡢ⤖ᯝ (Fig.2)࠿ࡽᤄධࡍࡿGlyࡢᩘࡀቑ࠼ࡿ
࡟ࡋࡓࡀࡗ࡚࣊ࣜࢵࢡࢫ㔞ࡀῶᑡࡋ࡚࠸ࡿࡇ࡜ࡀ☜ㄆ࡛ࡁࡓࠋ
ࡇࡢ⤖ᯝ࠿ࡽࠊ࣮ࣝࣉෆࡢṧᇶᩘࡀቑ࠼ࡿ࡜ྍ⬟࡞ࢥࣥࣇ࢛࣓
࣮ࢩࣙࣥᩘࡀቑຍࡋࠊ࣊ࣜࢵࢡࢫࡢ᰾ᙧᡂ☜⋡ࡀపୗࡍࡿ࡜࠸
࠺⪃࠼࡟୍⮴ࡋࡓࠋࡲࡓࠊNMRࡢ஧ḟ໬Ꮫࢩࣇࢺࡢ⤖ᯝ࠿ࡽࠊ࣊ࣜࢵࢡࢫ㡿ᇦࡣྠ୍࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࠊᴫࡡᤄධࡍࡿGlyࡢᩘࢆቑࡸࡍࡈ࡜࡟ࢩࣇࢺࡍࡿ㔞ࡀῶᑡࡋࡓࡇ࡜ࡀ☜ㄆ࡛ࡁࡓࠋ
į2D ࡜ ncSPC ࡟ ࡼ ࡾ ⟬ ฟ ࡋ ࡓ ࣊ ࣜ ࢵ ࢡ ࢫ ᙧ ᡂ ๭ ྜ

Fig.2 CD spectra(Fig.3 ,Fig.4)ࢆ☜ㄆࡍࡿ࡜ࠊ࡝ࡕࡽࡶGlyࢆᤄධࡋࡓࡇ࡜࡛ࣝ

࣮ࣉࡢ୰࡛ࡢ࣊ࣜࢵࢡࢫࡢ᰾ᙧᡂࡀࡋ࡟ࡃࡃ࡞ࡗࡓࡇ࡜ࠊGlyࢆᤄධࡋࡓ࿘ᅖࡢ࣊ࣜࢵࢡࢫ㔞ࡀ≉࡟኱ࡁࡃῶࡗࡓࡀࠊGlyࢆᤄධࡋࡓ࿘ᅖࡔࡅࡀᔂቯࡍࡿࠊ࠶ࡿ࠸ࡣ∦ഃࡢ࣊ࣜࢵࢡࢫࡢࡳࡀᔂቯࡍ
ࡿࡢ࡛ࡣ࡞ࡃࠊ඲యⓗ࡟࣊ࣜࢵࢡࢫࡢᙧᡂ๭ྜࡀୗࡀࡿ࡜࠸࠺ࡇ࡜ࡀ☜ㄆ࡛ࡁࡓࠋᚑࡗ࡚ࠊGlyࢆᤄධࡋ࡚࣮ࣝࣉ㡿ᇦࢆᘏ㛗ࡋࡓࡇ࡜࡟ࡼࡗ࡚࣊ࣜࢵࢡࢫᮎ➃ࡢ⮬⏤ᗘࡀቑ࠼ࡓࡇ࡜࡛࣊ࣜࢵࢡࢫ
ࡢ᰾ᙧᡂࡀࡋ࡟ࡃࡃ࡞ࡗࡓࡓࡵࠊ࣊ࣜࢵࢡࢫࢆ࡜ࡿศᏊᩘࡀῶࡗࡓ࡜⪃࠼ࡽࢀࡿࠋ
ᮏ◊✲ࡢ⤖ᯝࡣࠊ࣮ࣝࣉࡢᙧᡂ࡟ࡼࡾ࣮ࣝࣉෆࡢ࣌ࣉࢳࢻ㙐ࡀྲྀࡾ࠺ࡿࢥࣥࣇ࢛࣮࣓࣮ࢩࣙࣥ
ᩘࡀῶᑡࡋ࣊ࣜࢵࢡࢫࡢ᰾ᙧᡂࡀಁ㐍ࡉࢀࡿࠊ࡜࠸࠺௬ㄝࢆᐃᛶⓗ࡟ࡣᨭᣢࡍࡿࡶࡢ࡛࠶ࡗࡓࠋ
CDࢫ࣌ࢡࢺࣝࡢ ᗘ౫Ꮡᛶ(⇕㌿⛣)࡜ࡶẚ㍑ࡋ࡞ࡀࡽࠊ࣊ࣜࢵࢡࢫᙧᡂ๭ྜࡢᐃ㔞ᛶ࡟ࡘ࠸࡚㆟ㄽࡍࡿணᐃ࡛࠶ࡿࠋ

Fig. 4 ncSPC score

Fig. 3 Helical fraction (į2D)
References[1] Nakagawa, K., Yamada, Y., Fujiwara, K., and Ikeguchi, M. (2007) J. Mol. Biol. 367, 1205-1214[2] Yamamoto, M., Nakagawa, K., Fujiwara, K., Shimizu, A., and Ikeguchi, M. (2011) Biochemistry 50,
10590-10597[3] Wishart, D. S., Bigam, C. G., Holm, A., Hodges, R. S., and Sykes, B. D. (1995) J. Biomol. NMR 5, 6781
[4] Camilloni, C., De Simon, A., Vranken, F., and Vendruscolo, M. (2012) Biochemistry 51, 2224-2231[5] Tamiloa, K., & Mulder, F. A. A. (2012) Biochem. Soc. Trans., 40, 1014-1020－ 251 －

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Figure 2: Temperature dependence of (a) Gº and (b) V inpressure denaturation of rWT () and rV30M ().
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

－ 253 －

P52Y

ࢫࢠཬࡧࢭ࢖ࣚ࢘࢖ࢺࢫࢠⰼ⢊⏤᮶GRP࢔ࣞࣝࢤࣥࡢ
❧యᵓ㐀ゎᯒ
ࠐ㣤ሯ཭⳯ࠊ㒯㟹ᗣࠊஂ⡿⏣༤அࠊ⇃ᮌᗣ⿱ࠊⰼᒸᮥ⨾ࠊྜྷᕝ୍Ṍࠊ୰ᔱ཭⌮ᯞࠊ▼ཎ㣁㤿ࠊ┦ἑᬛᗣ
1໭ᾏ㐨኱Ꮫ኱Ꮫ㝔 ⏕࿨⛉Ꮫ㝔
2໭ᾏ㐨኱Ꮫ኱Ꮫ㝔 ඛ➃⏕࿨⛉Ꮫ◊✲㝔Structural analysis of GRP allergens from European cypress and Japanese ceder pollen‫ۑ‬Tomona Iizuka1, Jingkang Zheng1, Hiroyuki Kumeta2, Yasuhiro Kumaki1, Ami Hanaoka1, Ichiho
Yoshikawa1, Yurie Nakajima1, Soma Ishihara1, Yomoyasu Aizawa2
1

Graduate School of Life Science, Hokkaido University

2 Faculty of Advanced Life Science, Hokkaido University

GRP (gibberellin-regulated protein) allergens from Cupressaceae pollen are cross-reactive with certain fruit
GRP allergens, causing pollen food allergy syndrome (PFAS). Structural analysis is important for elucidating
the mechanism of PFAS because the similarity of conformation contributes to cross-reactivity. In this study,
we carried out overexpression and three-dimensional structural analysis of Japanese cedar (Cryptomeria
japonica) and European cypress (Cupressus sempervirens) GRP. An isotope-labeled sample was preparedusing Pichia pastoris and subjected to NMR three-dimensional structural analysis. As a result, the threedimensional structure of the pollen GRP allergen was determined for the first time, revealing a stable structurein which six disulfide bonds are preserved. We compared the structure of peach GRP, which causes PFAS,
and examined the causes of cross-reactivity and differences in allergenicity.
ʴഐ‫ܢ‬ʵ
ϐόΫՌ͹ध໨͹՘ฆͺɼೖຌ͹ηά(Cryptomeria japonica)ࠊ࣮ࣚࣟࢵࣃࡢࢭ࢖ࣚ࢘࢖ࢺࢫࢠ
(Cupressus sempervirens)͵ʹ༹ʓ͵ஏҮͲ॑གྷ͵ΠϪϩάʖ͹‫ݬ‬Ҿͳ͵ͮͱ͏ΖɽΉͪɼ՘ฆͳՎ
ࣰ౵Ͷ‫؜‬ΉΗΖΠϪϩΰϱ͹‫ڠ‬௪Φϒφʖϕ͗‫ݬ‬Ҿͳ͵ͮͱӀً͘͞͠ΗΖ3)$6ʤ՘ฆৱ෼ΠϪϩάʖ঳ޫ‫܊‬ʥͺɼ॑ಠ͵સਐ঳য়ΝӀًͤ͘͞৖߻΍͍Εɼ৆ࡋ͵‫ݬ‬Ҿմ໎ΏΓΕ੠ౕ͹߶͏ਏஇʀ࣑ྏ๑͹֋൅͗๮ΉΗΖɽζϗϪϨϱ௒ઇνϱϏέ࣯ʤJLEEHUHOOLQUHJXODWHGSURWHLQɾ*53ʥϓΟϝϨʖͶ଒ͤΖ&XSV ι΢ϦΤ΢φηά՘ฆ༟པ ɼ&U\ M ʤηά՘ฆ༟པʥͺ3)$6͹‫ݬ‬Ҿͳ͵ΖΠϪϩΰϱ͹ҲझͲɼϠϠ͵ʹ͹Վ෼*53ͳިࠫൕԢ੓Ν࣍ͯɽ*53ͺ༁ N'D ఖౕͳ‫ع‬எ͹3)$6‫ݬ‬ҾΠϪϩΰϱͳർֳ͢ͱఁ෾ࢢ͵͗Δɼ༁࢔‫خ‬͹αΠߑଆ஦Ͷ߶ౕͶฯଚ͠Ηͪຌ͹ζηϩϓΡχ݃߻Ν༙
ͤΖͳ͏͑ಝ௅͍͗Ζɽ)LJͶࣖͤΓ͑Ͷɼεητ΢ϱҐ֐͹ഓ྽ฯଚ੓΍߶͚ɼ՘ฆ༟པͳՎ
ࣰ༟པؔͶ͕͏ͱ΍Ґ৏͹ഓ྽ྪࣇ੓Νࣖͤɽ͖͢͢ɼ߶͏ഓ྽૮ಋ੓ΝࣖͤͶ΍͖͖ΚΔ
ͥΠϪϩάʖ੓Ν༙͢͵͏ζϡΪ΢Ϡ*53ʤVQDNLQʥ͗எΔΗͱ͕Εɼཱིରߑଆ͹Κ͖ͥ͵ࠫҡ͗ΠϪϩάʖ੓ΏިࠫൕԢ੓Ͷ‫ؖ‬༫͢ͱ͏Ζͳߡ͓ΔΗͱ͏Ζɽͨ͹ͪΌຌ‫Ͳڂݜ‬ͺ&XS V ͳ&U\ M ͹ϨαϱϑψϱφνϱϏέ࣯Νࡠ੣͢ͱ105ཱིରߑଆմ
ੵΝߨ͏ɼΦϒφʖϕ෨Ғ͵ʹͶͯ͏ͱ‫ݗ‬౾ͪ͢ɽ
ࢪ࣋ࣞࣜࣥㄪ⠇ࢱࣥࣃࢡ㉁ࠊࢪࢫࣝࣇ࢕ࢻ⤖ྜ‫ࢃ࠿ࡋࡼࠊࡳ࠶࠿࠾࡞ࡣࠊࢁࡦࡍࡸࡁࡲࡃࠊࡁࡺࢁࡦࡓࡵࡃࠊ࠺ࡇ࠸ࡏ࠸࡚ࠊ࡞ࡶ࡜࠿࡙࠸࠸ۑ‬࠸ࡕ࡯ࠊ࡞࠿ࡌࡲࡺࡾ࠼ࠊ࠸ࡋࡣࡽࡑ࠺ࡲࠊ࠶࠸ࡊࢃ࡜ࡶࡸࡍ

－ 254 －

Fig. 1. Multiple sequence alignments of GRP allergens
Sequence alignment of GRP allergens of cedar, cypress, peach, pomegranate, and orange. Cysteines forming
disulfide bonds are connected by lines.

ʴࣰ‫ݩ‬ʵ&XSV͕Γ;&U\M͹ҪఽࢢΝS3,&ϗένʖͶૢ೘͢ɼϟνόʖϩࣁԿ߮฾3SDVWRULVΝ‫ܙ‬࣯఺‫ͪ͢׷‬ɽ͞ΗΔ͹*53ͺ͖̔ॶ͹ζηϩϓΡχ݃߻Ν‫ܙ‬੔ͤΖ෵ࡸ͵ߑଆΝ༙ͤΖͪΌɼਇ֫ਫ਼෼Ͳ͍Ζ߮฾͹෾ൽ൅‫ܧݳ‬Νમ୔ͪ͢ɽ੠੣ͺཇ΢Ψϱި‫׷‬έϫϜφήϧϓΡʖͳ‫ٱ‬૮
+3/&ͲߨͮͪɽඬࣟԚԿΠϱϠωΤϞΝ஢ો‫ͱ͢ͳݱ‬1ඬࣟΝࢬͪ͢ϨαϱϑψϱφνϱϏέ
࣯Νਫ਼ࢊ͢ɼ105଎ఈͶ༽͏ͪɽ੠੣ࡃ͹ಋҒରඬࣟ&XSVɼ&U\MΝ'2Ͷ༻մ͢ͱS+Ͷ௒੣ͪ͢ɽඬࣟ1‫;ٶ‬ళષଚࡑർ͹&Ν༽͏್࣏ͪ‫͕ݫ‬Γ;ࢀ࣏‫ݫ‬105଎ఈΝ$9$1&(1(2  0+]ʤ%UXNHUʥΝ༽͏ͱߨͮͪɽͤ΄ͱ͹Πϝό࢐࢔‫خ‬͹क࠱‫ؾ‬଒Νߨͮͪ͹ͬɼ&<$1$͹12(‫ؾ‬଒ͳߑଆ‫ࢋܯ‬ͶΓΕཱིରߑଆΝ݀ఈͪ͢ɽಚΔΗཱིͪରߑଆΝ΍ͳͶ'LVFR7RSHΝ༽͏ͱΦϒφʖϕ෨ҒΝ༩଎ͪ͢ɽʴ݃Վʀߡࡱʵ
߮฾൅‫ߑܧݳ‬஛Ͷ੔ޯ͢ɼ՘ฆ঳‫݄ं׳‬ੜ஦͹,J(ͳ͹݃߻੓Ώళષ༟པ͹*53ͳ͹‫͖ʹ͵ݩࣰ߻ڟ‬ΔɼಚΔΗͪνϱϏέ࣯͗ΠϪϩΰϱͳ͢ͱΦϒφʖϕΝཱི༙ͪ͢ରߑଆ
Ν‫ܙ‬੔͢ͱ͏Ζ͞ͳΝ֮೟ͪ͢ɽಋҒରඬࣟνϱϏέ࣯ͺ
കஏ /͍ͪΕfPJಚΔΗͪɽ
105մੵͶΓΕɼ)LJͶཱིࣖͤରߑଆ͗݀ఈ͠Ηɼຌ͹ЍϖϨρέη͗͖ॶ͹ζηϩϓΡχ݃߻Ͳ‫ݽ‬ఈ͠Ηͪ

Fig. 2. Determined 3D structureߑଆ֮͗೟͠Ηͪɽ݀ఈ͠ΗཱིͪରߑଆΝ΍ͳͶͪ͢Φϒ

of Cup s 7

φʖϕ෨Ғ͹༩଎Ͳͺɼ͖ॶ͹ߑଆదΦϒφʖϕ෨Ғ͗Residues with high epitope໚ͶॄΉΖΓ͑͵ߑଆ͗ΊΔΗɼ͞ΗΔ͹Φϒφʖϕ෨Ғ

prediction scores in DiscoTope 2.0͗‫ڠ‬ಋ͢ͱ໖Ӻࡋ๖Ν࢙ܻ͢ͱ͏ΖՆ೵੓͗ࣖࠨ͠Ηͪɽare represented in dark gray color.







－ 255 －

P53

ࣉࣟࢺࣥఏᑟᛶ࢔ࣝࢠࣥ㓟/2-࢔ࣝ࢟ࣝ࢖࣑ࢲࢰ࣮ࣝ」ྜయࡢศᏊ
㐠ື࡜ᒁᡤᵓ㐀‫ۑ‬⣽Ụ⳯ࠎⰼ1㸪ᰩཎᣅஓ1㸪㔜⏣Ὀᏹ2㸪㞵᳃⩧ᝅ2㸪஭⏣᭸ᬛ1㸪Ỉ㔝ඖ༤1,2
1㔠ἑ኱Ꮫ࣭኱Ꮫ㝔⮬↛⛉Ꮫ◊✲⛉
2㔠ἑ኱Ꮫ࣭ࢼࣀ࣐ࢸࣜ࢔ࣝ◊✲ᡤ

Molecular Motion and Local Structure of Proton Conducting Alginic Acid/2Alkylimidazole Composites‫ۑ‬Nanaka Hosoe1, Takuya Kurihara1, Yasuhiro Shigeta2, Shogo Amemori2, Tomonori Ida1, Motohiro
Mizuno1,21Graduate School of Natural Science and Technology, Kanazawa University

2 NanoMaterials Research Institute, Kanazawa University

Alginic acid (AA) /imidazole (Im) composites have been reported as solid electrolytes with high proton
conductivity at high temperatures [1]. The reorientational motion of Im is considered to enable efficient
proton conduction. However, the molecular motion of Im has not been clarified, the knowledge about it isexpected. In this study, AA/Im and AA/2-alkylimidazole (AlkIm) composites were used. We investigated
the relationship between the proton conductivity and molecular motion by using solid NMR. At low
temperatures, AA/Im showed higher proton conductivity than AA/AlkIm. AlkIm molecules are stationary,
but Im molecule is in 180° flip motion at room temperature. Such a difference in the motility of proton carrier
molecules is thought to affect proton conductivity.
࠙ᗎㄽࠚ100Υ௨ୖ࡛㧗࠸ࣉࣟࢺࣥఏᑟᛶࢆ♧ࡍᅛయ㟁ゎ㉁࡜ࡋ࡚࢖࣑ࢲࢰ࣮ࣝ(Im)࡜㧗ศᏊࡢ」ྜయ
ࡀሗ࿌ࡉࢀ࡚࠾ࡾࠊࡑࡢ㸯ࡘ࡟Im࡜࢔ࣝࢠࣥ㓟(AA)ࡢ」ྜయAA-xIm (x㸸AAࡢ࢝ࣝ࣎࢟ࢩᇶ࡟ᑐ
ࡍࡿImࡢࣔࣝẚ)ࡀ࠶ࡿ[1]ࠋAA-xImࡢࣉࣟࢺࣥఏᑟࡣࠊImࡀ࢟ࣕࣜ࢔࡜࡞ࡿࣉࣟࢺࣥ࣍ࢵࣆࣥࢢ
(ࢢ࣮ࣟࢱࢫᶵᵓ)࡛ᨭ㓄ࡉࢀ࡚࠾ࡾࠊImࡢ෌㓄ྥ㐠ືࡀຠ⋡ⓗ࡞ࣉࣟࢺࣥఏᑟ࡟㛵୚ࡍࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿࠋࡇࢀࡽࡢ」ྜయ⭷ࡢ⇕Ᏻᐃᛶࢆྥୖࡉࡏࡿࡓࡵ࡟ࡣࠊࣉࣟࢺࣥ࢟ࣕࣜ࢔ศᏊࡢ㧗࡛ࡢ㞳⬺ࢆ㜵ࡄࡇ࡜ࡀᚲせ࡛࠶ࡿࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊ࢔ࣝ࢟ࣝ㙐ࡀ࢔࣮ࣥ࢝࡜ࡋ࡚ാࡃࡇ࡜ࢆ
ᮇᚅࡋࠊImࡢ2఩࡟㛗ࡉࡢ␗࡞ࡿ࢔ࣝ࢟ࣝ㙐ࢆ᭷ࡍࡿImㄏᑟయ(AlkIm)࡜AAࡢ」ྜయ⭷AAxAlkImࢆㄪ〇ࡋࠊࣉࣟࢺࣥఏᑟᛶ࡜⇕Ᏻᐃᛶࢆㄪ࡭ࡓࠋ4✀㢮ࡢAlkIm (Fig 1ࠊᕥ࠿ࡽ࣓ࢳࣝ࢖࣑
ࢲࢰ࣮ࣝ(MeIm)ࠊ࢚ࢳࣝ࢖࣑ࢲࢰ࣮ࣝ(EtIm)ࠊࣉࣟࣆࣝ
࢖࣑ࢲࢰ࣮ࣝ(PrIm)ࠊࣈࢳࣝ࢖࣑ࢲࢰ࣮ࣝ(BuIm))࡜Imࢆ
⏝࠸ࠊࣉࣟࢺࣥ࢟ࣕࣜ࢔ศᏊࡢᵓ㐀࡜ࣉࣟࢺࣥఏᑟᛶࡢ
㛵ಀࢆㄪ࡭ࡓࠋࡲࡓࠊᅛయ2H NMR ᐃ࡟ࡼࡗ࡚ࣉࣟࢺ
ࣥ࢟ࣕࣜ࢔ศᏊࡢ㐠ືࢆゎᯒࡋࠊࣉࣟࢺࣥఏᑟ࣓࢝ࢽ

Fig. 1. Structure of alkylimidazoles.

ࢬ࣒ࢆ⪃ᐹࡋࡓࠋ
ࣉࣟࢺࣥఏᑟయ㸪㧗ศᏊ」ྜయ⭷㸪ᅛయ㔜Ỉ⣲NMR‫࠿࡞࡞࠼ࡑ࡯ۑ‬㸪ࡃࡾࡣࡽࡓࡃࡸ㸪ࡋࡆࡓࡸࡍࡦࢁ㸪࠶ࡵࡶࡾࡋࡻ࠺ࡈ㸪࠸ࡔ࡜ࡶࡢࡾ㸪ࡳࡎࡢࡶ࡜ࡦࢁ

－ 256 －࠙ᐇ㦂ࠚImཬࡧAlkIm࡜AAࢆ⵨␃Ỉ୰࡛ࣔࣝẚ1:1ࡢ๭ྜ࡛ΰྜࡋࠊᩘ᪥㛫஝⇱ࡉࡏࡿࡇ࡜࡛ⷧ⭷ࢆᚓࡓࠋᚓࡽࢀࡓ」ྜయ⭷ࢆ50Υ࡛24᫬㛫┿✵஝⇱ࡋࠊࡑࢀࡒࢀࡢ⭷࡟ࡘ࠸࡚஺ὶ࢖ࣥࣆ࣮ࢲࣥࢫἲ
࡟ࡼࡿࣉࣟࢺࣥఏᑟ⋡ ᐃࠊᅛయ2H NMR ᐃࢆ⾜ࡗࡓࠋᅛయ2H NMR ᐃࡣࠊࣉࣟࢺࣥ࢟ࣕࣜ࢔
࡛࠶ࡿImཬࡧAlkImࡢ㔜Ỉ⣲໬≀ࢆ⏝࠸࡚స〇ࡋࡓ」ྜయ⭷ࢆヨᩱ࡜ࡋࠊᅄᴟᏊ࢚ࢥ࣮(QE)ἲࢆ
⏝࠸ඹ㬆࿘Ἴᩘ45.825 MHz࡛⾜ࡗࡓࠋ࠙⤖ᯝ࣭⪃ᐹࠚ
Fig. 2࡟ྛ」ྜయ⭷࡟࠾ࡅࡿࣉࣟࢺࣥఏᑟ⋡ࡢ ᗘኚ໬ࢆ♧ࡍࠋAA-1AlkImࡣప ࡛ࡣ
AA-1Imࡼࡾప࠸ࣉࣟࢺࣥఏᑟ⋡ࢆ♧ࡋࡓࡀࠊ⣙393 K ௨ୖ࡛ఏᑟ⋡ࡀᛴ⃭࡟ୖ᪼ࡋࠊ
423 K࡛࡯ࡰ➼ࡋ࠸್࡜࡞ࡗࡓࠋ᭱኱ࡢఏᑟ
⋡ࢆ♧ࡍ ᗘࡣIm࡜MeImࡣ423 KࠊEtIm࡜
PrImࡣ443 KࠊBuImࡣ453 K࡛࠶ࡗࡓࠋIm࡟㛗㙐ࡢ࢔ࣝ࢟ࣝ㙐ࡀࡘࡃࡇ࡜࡛AA࠿ࡽ⬺㞳ࡋ࡟ࡃࡃ࡞ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
Fig. 3࡟AA-1ImࠊAA-1PrImࠊAA-1BuImࡢ
2H NMRࢫ࣌ࢡࢺࣝࡢ

ᗘኚ໬ࢆ♧ࡍࠋ295 K

࡛ࡣࠊAA-1PrIm࡜AA-1BuImࡣ㟼Ṇ≧ែࡢ⥺

Fig. 2. Temperature dependence ofᙧ(Pakeࣃࢱ࣮ࣥ)࡛࠶ࡗࡓࡀࠊAA-1Imࡣ㟼Ṇ

proton conductivity.

≧ែࡢࢫ࣌ࢡࢺࣝ࡜Im ࡢ180r
ࣇࣜࢵࣉࡢࢫ࣌ࢡࢺࣝࡢ㊊ࡋྜ

(a)

(b)

(c)

ࢃࡏ࡛෌⌧ࡉࢀࡓࠋࡇࡢࡇ࡜࠿
ࡽࠊImࡣAlkImࡼࡾࡶప ࠿ࡽ㐠ືࡀ㉳ࡇࡗ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡇࡢࣉࣟࢺࣥ࢟ࣕࣜ࢔
ศᏊࡢ㧗࠸㐠ືᛶࡀࠊAA-1Imࡀప࠿ࡽ㧗࠸ࣉࣟࢺࣥఏᑟᛶࢆ

♧ࡍ୍ᅉ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ
AA-1PrIm࡜AA-1BuIm࡟ࡘ࠸࡚ࡣࠊ353 K௨ୖ࡛ࡣ㟼Ṇ≧ែࠊ

Fig. 3. Temperature dependence of 2H NMR spectra for (a) AA-1Im,Im⎔ࡢ180rࣇࣜࢵࣉࠊ࢔ࣝ࢟

(b)AA-1PrIm, (c) AA-1BuIm. Black lines show simulation spectra.

ࣝ㙐ࡢᅇ㌿ⓗ᣺ືࠊ➼᪉ᅇ㌿ࡢࢫ࣌ࢡࢺࣝࡢ㊊ࡋྜࢃࡏ࡛෌⌧ࡉࢀࠊ393 K௨ୖ࡛ࡣ➼᪉ᅇ㌿ࡢࢩ࣮ࣕࣉ࡞ᡂศࡀᨭ㓄ⓗ࡜࡞ࡗࡓࠋ➼᪉ᅇ㌿ࡀᨭ㓄ⓗ࡜࡞ࡗࡓ ᗘࡣࣉࣟࢺࣥఏᑟ⋡ࡀᛴ⃭࡟ୖ᪼ࡍࡿ ᗘ࡜୍⮴ࡋ࡚࠾ࡾࠊࣉ
ࣟࢺࣥ࢟ࣕࣜ࢔ศᏊࡢ㐠ືᛶࡢྥୖࡀఏᑟ⋡ୖ᪼ࡢ୍ᅉ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ
࠙ཧ⪃ᩥ⊩ࠚ
[1] M. Yamada and I. Honma, Polymer. 46, 2986 (2005).

－ 257 －

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P55

In-cell NMR࡟ࡼࡿKeap1/Nrf2⣔ࡢ◊✲‫ۑ‬㇏⏣ⱆ⏕㸪⊦⫤᫭௓㸪ᮎᗈᚿ⧊㸪ᓥ ᾏ⩧㸪ụ㇂㕲ර㸪㕥ᮌ㝯ྐ2㸪
ᒣᮏ㞞அ2,3㸪ఀ⸨ 㝯1ᮾி㒔❧኱Ꮫ࣭኱Ꮫ㝔⌮Ꮫ◊✲⛉2ᮾ໭኱Ꮫ࣭኱Ꮫ㝔་Ꮫ◊✲⛉3ᮾ໭࣓ࢹ࢕࣭࣓࢝ࣝ࢞ࣂࣥࢡᶵᵓ

An in-cell NMR study of the Keap1-Nrf2 system‫ۑ‬Mei Toyoda1, Kohsuke Inomata1, Shiori Suehiro1, Kaito Shima1, Teppei Ikeya1, Takafumi Suzuki2,
Masayuki Yamamoto2,3, and Yutaka Ito1
1 Department of Chemistry, Tokyo Metropolitan University; 2 Department of Medicine, Tohoku University;
3 Tohoku University Tohoku Medical Megabank organization

The Kelch-like ECH-associated-protein 1 (Keap1) – NF-E2-related factor 2 (Nrf2) system is central tomammalian cellular protection against electrophiles and oxidative stress and is a drug target for disease
prevention and treatment. Previous studies have proposed the two-site substrate recognition model for the
Keap1-Nrf2 system, known as “Hinge-Latch model”. The Keap1-Nrf2 interaction is known to be alteredunder “non-stress” or “stress” condition, but the mode has not been examined in detail in intracellularenvironment. Aiming at understanding the Hinge-Latch model in detail in living cells, we have initiated incell and in-diluted solution NMR studies. In-cell NMR spectroscopy is currently the only approach that can
provide information of protein behaviours inside cells at atomic resolution. In addition to human cultured
HeLa cells, we employed some cell lines with disease background as host cells.
䛆ᗎㄽ䛇
Keap1-Nrf2⣔䛿䠈ぶ㟁Ꮚᛶ≀㉁䜔㓟໬䝇䝖䝺䝇䛾䝉䞁䝃䞊䛷䛒䜚䠈䝴䝡䜻䝏䞁E3䝸䜺䞊䝊䛾䜰䝎䝥䝍䞊ศᏊ䛷䜒䛒䜛Keap1䛸䠈㌿෗ᅉᏊNrf2䛛䜙䛺䜛䠈⏕య㜵ᚚ㑇ఏᏊ⩌䛾Ⓨ⌧ไᚚ䝅䝇䝔䝮䛷䛒䜛䠊
Keap1஧㔞య䛿Cᮎ➃䛾DC㡿ᇦ䠄Keap1-DC䠅䜢௓䛧䛶䠈Nrf2䛾Nᮎ➃Neh2㡿ᇦ䠄Nrf2-Neh2䠅䛻䛒䜛2䛴䛾䝰䝏䞊䝣䠄DLG䛸ETGE䠅䛸⤖ྜ䛩䜛䠊㠀䝇䝖䝺䝇᮲௳ୗ䛷䛿䠈Nrf2䛿Keap1䜢௓䛧䛶㎿㏿䛻䝴
䝡䜻䝏䞁䠄Ub䠅໬䛥䜜䠈䝥䝻䝔䜰䝋䞊䝮䛷ศゎ䛥䜜䜛䠊୍᪉䝇䝖䝺䝇᮲௳ୗ䛷䛿䠈Keap1䜢௓䛧䛯Nrf2䛾
Ub໬䛜ῶᙅ䛩䜛䛣䛸䛷ศゎ䛜ᅇ㑊䛥䜜䠈Nrf2䛿᰾ෆ⛣⾜䛧䛶ᶆⓗ㑇ఏᏊ⩌䛾㌿෗䜢ㄏᑟ䛩䜛䠊
Keap1-Nrf2┦஫స⏝䛻㛵䛧䛶䛿䠈DLG䛾䜏䛜஋㞳䛩䜛䛂㛜䛸⼖␒䝰䝕䝹䛃[1,2]䛜ᥦၐ䛥䜜䛶䛔䜛䛜䠈䛣䜜䜢⏕䛝䛯⣽⬊䛾୰䛷ヲ⣽䛻᳨ド䛧䛯䛔䠊୍᪉䛷䠈Keap1-Nrf2⤖ྜ㒊఩䛾య⣽⬊ኚ␗䠄䛜䜣ᝏᛶ໬䛻ᐤ୚䠅䜢᭷䛩䜛⫵䛜䜣⣽⬊ᰴ䜔䠈p62䠄Keap1-Nrf2⤖ྜ䜢㜼ᐖ䠅䛜⵳✚䛧䛯⫢䛜䜣⣽⬊ᰴ䛺䛹䛜☜❧䛥䜜䛶䛚䜚䠈䛣䜜䜙䛂⑌⑓䛾⫼ᬒ䜢䜒䛴䛃⣽⬊୰䛷䛾Keap1-Nrf2⣔䛾ゎᯒ䛻䜒኱䛝䛺ព⩏䛜䛒䜛䠊䛭䛣䛷䠈⏕⣽⬊୰䛷䛾⺮ⓑ㉁㛫┦஫స⏝䜢ཎᏊ䝺䝧䝹䛷ゎᯒྍ⬟䛺in-cell NMR䜢㐺⏝䛩䜛䛣䛸䛷䠈✀䚻䛾⣽⬊䛷䛾keap1-Nrf2┦஫స⏝䛾ヲ⣽䛻㏕䜛䛣䛸䜢┠ᣦ䛧䛯䠊___________________________________________________________________________________
In-cell NMR㸪Keap1-Nrf2⣔㸪ࣂ࢖࢜ࣜ࢔ࢡࢱ࣮‫࠸ࡵ ࡔࡼ࡜ۑ‬㸪࠸ࡢࡲࡓ ࡇ࠺ࡍࡅ㸪ࡍ࠼ࡦࢁ ࡋ࠾ࡾ㸪ࡋࡲ ࠿࠸࡜㸪࠸ࡅࡸ ࡚ࡗ࡮࠸㸪ࡍࡎࡁ ࡓ࠿ࡩࡳ㸪ࡸࡲࡶ࡜ ࡲࡉࡺࡁ㸪࠸࡜࠺ ࡺࡓ࠿－ 260 －

䛆ᐇ㦂䛇In-cell NMRᐇ㦂䛷䛿䠈኱⭠⳦ෆⓎ⌧⣔䜢⏝䛔䛶ㄪ〇䛧䛯¹ၫNᶆ㆑Nrf2-Neh2䜢䠈㟁Ẽ✸Ꮝἲ䜢⏝䛔䛶⣽⬊ෆ䛻ᑟධ䛧䠈᪂㩭䛺ᇵ㣴⁐ᾮ䜢ᖖ䛻౪⤥䛩䜛䛣䛸䛜䛷䛝䜛䝞䜲䜸䝸䜰䜽䝍䞊䝅䝇䝔䝮䜢฼⏝䛧䛴
䛴䠈2D ¹H-¹ၫN SOFAST-HMQC䝇䝨䜽䝖䝹䛾 ᐃ䜢⾜䛳䛯䠊
䜎䛪䠈Nrf2䛜␗ᖖάᛶ໬䛧䛶䛔䜛䛜䜣⣽⬊䛸䛧䛶䠈HeLa⣽⬊䜢౑⏝䛧䛶ᐇ㦂䜢⾜䛳䛯䠊䛣䛾᫬䝥䝻䝔䜰䝋䞊䝮ศゎ䛻䜘䜛ᙳ㡪䜢☜ㄆ䛩䜛䛯䜑䛻䠈䝥䝻䝔䜰䝋䞊䝮㜼ᐖ๣MG132Ꮡᅾୗ䛷in-cell NMRᐇ㦂䜢⾜䛔䠈䛥䜙䛻Ub໬䛾᭷↓䛻䜘䜛ᙳ㡪䜢☜ㄆ䛩䜛䛯䜑䛻䠈㔝⏕ᆺ䠄Nrf2-Neh2-WT䠅䛻ຍ䛘䛶Nrf2-Neh2
䛾7䛴䛾Lysṧᇶ䜢Arg䛻⨨᥮䛧䛯ኚ␗య(Nrf2-Neh2-R7)䜒⏝䛔䛯䠊ḟ䛻䠈Keap1䛾Nrf2┦஫స⏝㒊఩䛻䛒䜛ኚ␗(Keap1-G333C)䛻䜘䛳䛶Keap1-Nrf2┦஫స⏝䛜ᙅ䜎䛳䛶䛔䜛A549⣽⬊[3]䛸䠈Keap1䛜Ꮡᅾ䛧䛺䛔MEF(Keap1-KO)⣽⬊䜢౑⏝䛧䠈䛭䜜䛮䜜MG132Ꮡᅾୗ䛷in-cell NMRᐇ㦂䜢⾜䛳䛯䠊䛆⤖ᯝ䛸⪃ᐹ䛇䛇
HeLa⣽⬊䛻䛚䛡䜛Nrf2-Neh2-WT䛾ᐇ㦂䛷䛿䠈Ⰻዲ䛺䝇䝨䜽䝖䝹䛾ྲྀᚓ䛻䛿⮳䜙䛺䛛䛳䛯䛜䠈
MG132Ꮡᅾୗ䛷䛿䠈Nrf2-Neh2⏤᮶䛾䝇䝨䜽䝖䝹䛾ほ 䛻ᡂຌ䛧䛯(FFig.1a)䠊䛣䛾䛣䛸䛛䜙䝥䝻䝔䜰䝋䞊䝮ศゎ䛜ᙳ㡪䜢䛚䜘䜌䛧䛶䛔䜛䛣䛸䛜䜟䛛䛳䛯䠊
Nrf2-Neh2-R7䛿Ub໬䛜㉳䛣䜙䛺䛔䛯䜑䠈MG132䛺䛧䛷䜒ศゎ䛥䜜䛺䛔䛸ண᝿䛧䛯䛜䠈ண᝿䛻཯䛧䛶Ⰻዲ䛺䝇䝨䜽䝖䝹䛿ほ䝖䝹䛾ほ䛥䜜䛪䠈Nrf2-Neh2-WTྠᵝ䠈MG132Ꮡᅾୗ䛷䛾䜏Nrf2-Neh2⏤᮶䛾䝇䝨䜽䛻ᡂຌ䛧䛯(F
Fig.1b)䠊䛣䛾䛣䛸䛛䜙䠈Ub໬䛾᭷↓䛻㛵䜟䜙䛪䝥䝻䝔䜰䝋䞊䝮ศゎ䛜㛵୚䛧䛶䛔䜛䛣䛸䛜♧၀䛥䜜䛯䛯䜑䠈௨㝆䛾ᐇ㦂䛿MG132Ꮡᅾୗ䛷⾜䛳䛯䠊䛥䜙䛻䠈Nrf2-Neh2-WT䛸ẚ㍑䛩䜛䛸䠈
Nrf2-Neh2-R7䛷䛿୍㒊䛾䝅䜾䝘䝹䛾ᾘኻ䛜ほ

䛥䜜䛯(F
Fig.1
1 㒊ศᅗ)䠊ᾘኻ䛿୺䛻Nrf2-Neh2䛾

DLG䛸ETGE䝰䝏䞊䝣䛷☜ㄆ䛥䜜䛯䛣䛸䛛䜙䠈䛣䜜䛿Nrf2-Neh2-R7䛿Ub໬䜢㜼ᐖ䛥䜜䛯䛣䛸䛻䜘䛳䛶
Keap1஧㔞య䠄~140kDa䠅䛸䜘䜚ᙉ䛟⤖ྜ䛧䠈ぢ䛛䛡䛾ศᏊ㔞䛜኱䛝䛟䛺䛳䛯䛯䜑䛷䛒䜛䛸⪃ᐹ䛧䛯䠊
䛥䜙䛻䠊A549⣽⬊䛾Keap1-G333Cኚ␗䛜Keap1-Nrf2┦஫స⏝䛻ᙳ㡪䜢୚䛘䛶䛔䜛䛛䜢☜ㄆ䛧䛯䠊
Nrf2-Neh2-R7䛷䛿┦஫స⏝䛾ῶᙅ䛻䜘䜚HeLa⣽⬊䜘䜚䜒Ⰻዲ䛺䝇䝨䜽䝖䝹䛜ほ 䛷䛝䜛䛸ண᝿䛧䛯䛜䠈᭷ព䛺ᕪ䛿ぢ䜙䜜䛺䛛䛳䛯䠊䛣䛾ཎᅉ䛸䛧䛶䠈ձA549⣽⬊䛾Keap1-G333Cኚ␗䛿Keap1-Nrf2┦஫స⏝䜢ᙅ䜑䜛䛾䛻䛿୙༑ศ䛷䛒䛳䛯䠈ղKeap1௨እ䛾ᅉᏊ䛜Nrf2-Neh2䛸┦஫స⏝䛧䛶䛔䜛䠈䛸䛔䛖2䛴䛾ྍ⬟ᛶ䛜⪃䛘䜙䜜䜛䠊ձ䛻䛴䛔䛶䛿䠈ᕼⷧ⁐ᾮ୰䛷䛾Nrf2-Neh2-WT/R7䛸Keap1-WT/G333C䛾ゎᯒ
䜢㏻䛧䛶Keap1-Nrf2┦஫స⏝䛻䛚䛡䜛G333C䛾ᙳ㡪䜢☜ㄆ䛩䜛䠊䜎䛯䠊ղ䛻䛴䛔䛶䠈MEF(Keap1KO)⣽⬊䛻䛚䛡䜛in-cell NMRᐇ㦂䜢㏻䛧䛶䠈Keap1௨እ䛾ᅉᏊ䛾ᐤ୚䜢☜ㄆ䛩䜛ィ⏬䛷䛒䜛䠊

Fig. 1 2D 1H-15N SOFAST-HMQC spectra of Nrf2-Neh2-WT (a) and Nrf2-Neh2-R7 (b) in HeLa cells in thepresence of a proteasome inhibitor MG-132.

References[1] Tong, K.I. et al. Mol. Cell. Biol. 27, 7511-7521 (2007); [2] Horie, Y. et al. Commun. Biol. 4, 576 (2021);[3] Singh, A. et al. PLOS. Medicine. 3, e420 (2006).

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HCVࢤ ࣀ ࣒RNA࡟ Ꮡ ᅾ ࡍ ࡿ ࢟ ࢵ ࢩ ࣥ ࢢ ࣝ ࣮ ࣉ ᵓ 㐀 ࡢ ゎ ᯒ‫␃ۑ‬Ᏺࡵࡄࡳ㸪Ἑྜ๛ኴ
༓ⴥᕤᴗ኱Ꮫ

Analysis of the kissing-loop structure in HCV genomic RNA‫ۑ‬Megumi Tomemori, Gota Kawai
Chiba Institute of Technology
Interactions between RNAs are known to have important functions. In hepatitis C virus(HCV), the kissing-loop interaction between the 5B-SL3.2 site at the 3' end of the NS5B geneand the Xtail-SL2 site in the 3' untranslated region is known to be involved in translational
regulation in the life cycle of HCV. In the present study, the interaction between the modelRNAs, 5BSL26 and XSL27 were analyzed by NMR. The solution structures of model RNAs
were determined individually, and, then, the formation of the complex was analyzed. It was
found that the stem structures in each RNA were retained in the complex, and the formation ofinter-molecular stem were confirmed by the analysis of imino proton signals.
ᗎㄽᮏ ◊ ✲ ࡛ ࡣ Cᆺ ⫢ ⅖ ࢘ ࢖ ࣝ ࢫ
㸦 HCV㸧 ࡢ ࢤ ࣀ ࣒ RNAࡢ 」 〇 ࡟࠾ ࡅ ࡿ RNA㛫 ┦ ஫ స ⏝ ࡢ ᙺ ๭ ࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋ࡚ 㸪 5B-SL3.2࡜ Xtail-SL2ࡢ 㛫 ࡟ண ᝿ ࡉ ࢀ ࡚ ࠸ ࡿ kissing-loop ┦஫స⏝࡟╔┠ࡋ㸪ࡑࡢ」ྜయࡢ
❧యᵓ㐀ࢆゎᯒࡋ㸪┦஫స⏝ᵝᘧࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜ࢆࡵࡊࡋ

Fig. 1. Possible interaction between 5BSL26 and XSL27࡚࠸ࡿ㸬ࡇ ࡢ ࡓ ࡵ ࡟ 㸪 5BSL3.2࠿ ࡽ 26ṧ ᇶ ࡢ ࢫ ࢸ ࣒ ࣝ ࣮ ࣉ ᵓ 㐀 ࡛ ࠶ ࡿ 5BSL26㸪 XtailSL2࠿ ࡽ 27
ṧ ᇶ ࡢ ࢫ ࢸ ࣒ ࣝ ࣮ ࣉ ᵓ 㐀 ࡛ ࠶ ࡿ XSL27ࢆ タ ィ ࡋ 㸦 Fig. 1㸧 㸪 NMRἲ ࡟ ࡼ ࡿ ❧ య ᵓ 㐀 ゎ ᯒࢆ 㐍 ࡵ ࡚ ࠸ ࡿ 㸬 ௒ ᅇ ࡣ 5BSL26࡜ XSL27࡟ ࡘ ࠸ ࡚ 㸪 ࡑ ࢀ ࡒ ࢀ ༢ య ࡛ ࡢ ❧ య ᵓ 㐀 ࢆ Ỵ ᐃ ࡋࡓࡢࡕ㸪୧⪅ࢆΰྜࡋࡓヨᩱࢆㄪ〇ࡋ㸪୺࡜ࡋ࡚࢖࣑ࣀࣉࣟࢺࣥࢩࢢࢼࣝࡢゎᯒ࡟ࡼࡗ࡚」ྜయࡢᙧᡂࢆゎᯒࡋࡓ㸬᪉ἲ㠀 ᶆ ㆑ RNAヨ ᩱ ࡣ 㸪 ໭ ᾏ 㐨 ࢩ ࢫ ࢸ ࣒ ࣭ ࢧ ࢖ ࢚ ࣥ ࢫ ♫ ࡟ ጤ ク ࡋ ࡚ ໬ Ꮫ ྜ ᡂ ࡋ ࡓ 㸬 ṧ ᇶ≉ ␗ ⓗ Ᏻ ᐃ ྠ ఩ య ᶆ ㆑ RNAヨ ᩱ ࡣ ኱ 㝧 ᪥ 㓟 ♫ ࡟ ጤ ク ࡋ ࡚ ໬ Ꮫ ྜ ᡂ ࡋ ࡓ 㸬 AvanceNeo600
ศ ග ィ 㸦 Bruker♫ 㸧 ࢆ ⏝ ࠸ 㸪 ⁐ ፹ ࡜ ࡋ ࡚ 㔜 Ỉ 㸦 99.98 atom%㸪 ኱ 㝧 ᪥ 㓟 ♫ 㸧 5 %࠾ ࡼ ࡧ 50
mM ሷ ໬ ࢼ ࢺ ࣜ ࢘ ࣒ ࢆ ྵ ࡴ 20 mM ࣜ ࣥ 㓟 ࢼ ࢺ ࣜ ࢘ ࣒ ⦆ ⾪ ᾮ 㸦 pH 6.5㸧 ࢆ ⏝ ࠸ ࡚ , 288 K
࡛ NMRࢫ ࣌ ࢡ ࢺ ࣝ ࢆᐃ ࡋ ࡓ 㸬 RNAࡢ ⃰ ᗘ ࡣ 㸪 0.13 mM࠿ ࡽ 0.29 mM࡛ ࠶ ࡗ ࡓ 㸬

Hepatitis C virus㸪Kissing-loop interaction‫ࡳࡄࡵࡾࡶࡵ࡜ۑ‬㸪࠿ࢃ࠸ࡈ࠺ࡓ

－ 262 －

⤖ᯝRNA༢ య ࡢ ゎ ᯒ 㸸 ࢖ ࣑ ࣀABࣉࣟࢺࣥࢫ࣌ࢡࢺࣝࡢゎᯒ࡟ ࡼ ࡾ 5BSL26࡜ XSL27ࡣ ࡑࢀࡒࢀணࡉࢀࡓ஧ḟᵓ㐀ࢆᙧᡂࡋ࡚࠸ࡿࡇ࡜ࡀ☜ㄆ࡛ ࡁ ࡓ 㸬 5BSL26࡛ ࡣ 㸪
NOE121ಶ 㸪 Ỉ ⣲ ⤖ ྜ ࡢ ㊥㞳 ᝟ ሗ 18ಶ 㸪 ஧ 㠃 ゅ 156ಶࢆᣊ᮰᮲௳࡜ࡋ࡚❧యᵓ㐀

Fig. 2. Secondary structure and the 10 lowest energy structuresィ⟬ࢆ⾜ࡗࡓ࡜ࡇࢁ㸪

A: 5BSL26, B: XSL27. Loop regions are indicated by light gray.

r.m.s.d.ࡀ 4.530s1.749㸦 ඲య 㸧 ࠾ ࡼ ࡧ 0.336s0.148㸦 ࢫ ࢸ ࣒ 㸧 ࡢ ᵓ 㐀 ࡀ ᚓ ࡽ ࢀ ࡓ 㸦 Fig. 2A㸧 㸬 XSL27࡛ ࡣ 㸪
NOE109ಶ 㸪 Ỉ ⣲ ⤖ ྜ ࡢ ㊥ 㞳 ᝟ ሗ 17ಶ 㸪 ஧ 㠃 ゅ 167ಶ ࢆ ᣊ ᮰ ᮲ ௳ ࡜ ࡋ ࡚ 㸪 r.m.s.d.ࡀ 6.881
s2.906㸦 ඲ య 㸧 ࠾ ࡼ ࡧ 0.299s0.116㸦 ࢫ ࢸ ࣒ 㸧 ࡢ ᵓ 㐀 ࡀ ᚓ ࡽ ࢀ ࡓ 㸦 Fig. 2B㸧 㸬 ࠸ ࡎ ࢀࡶ ࣝ ࣮ ࣉ 㒊 ศ ࡣ NOEࡀ ᑡ ࡞ ࡃ ᵓ 㐀 ࡣ ཰ ᮰ ࡋ ࡚ ࠸ ࡞ ࠿ ࡗ ࡓ 㸬
 」ྜయࡢゎᯒ㸸」ྜయ࡛ࡣ࢖࣑ࣀࣉࣟࢺࣥࢩࢢࢼࣝ㡿ᇦ࡟࠾࠸࡚ศᏊ㛫ࡢሷᇶᑐ࡟
⏤᮶ࡍࡿࢩࢢࢼࣝࡀほࡉ ࢀ ࡓ 㸦 Fig. 3㸪 *㸧 㸬 」 ྜ య ࡢ NOESYࢫ ࣌ ࢡ ࢺ ࣝ ࠿ ࡽ 」 ྜ య࡛ ࡣ AU-GC-AU࡜ 㐃 ⥆ ࡍ ࡿ ࢩ ࢢ ࢼ ࣝ ࡀ ほࡉ ࢀ ࡚ ࠾ ࡾ 㸦 Fig. 4㸪 ⥺ 㸧 㸪 Fig. 1࡟ ♧ ࡋ ࡓ ศᏊ㛫ࡢࢫࢸ࣒ᵓ㐀ࡀᙧᡂࡉࢀ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬⪃ᐹ
5BSL26࠾ ࡼ ࡧ XSL27ࡢ ༢ య ࡟ ࠾ ࠸ ࡚ ᙧ ᡂ ࡉ ࢀ ࡚ ࠸ ࡓ ࢫ ࢸ ࣒ ᵓ 㐀 ࡣ 㸪 ࡇ ࢀ ࡽ ࡢ 」 ྜ య࡟ ࠾ ࠸ ࡚ ࡶ ᙧ ᡂ ࡉ ࢀ ࡚ ࠸ ࡓ 㸬 ࡲ ࡓ 㸪 Fig. 1ࡢ ศ Ꮚ 㛫 ࢫ ࢸ ࣒ ࡟ ᑐ ᛂ ࡍ ࡿ ࢖ ࣑ ࣀ ࣉ ࣟ ࢺ ࣥ ࢩࡉ ࢀ ࡓ ࡇ ࡜ ࠿ ࡽ 㸪 5BSL26࡜ XSL27ࡣ ண ᝿ ࡉ ࢀ ࡓ ࢟ ࢵ ࢩ ࣥ ࢢ ᵓ 㐀 ࢆ ᙧ ᡂ ࡋࢢࢼࣝࡀほ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬」 ྜ య ࡢ ᙧ ᡂ ࡟ ࡣ ⃰ ᗘ ౫ Ꮡ ᛶ ࡀ ࡳ ࡽ ࢀ 㸪 0.1 mM⛬ ᗘ ࡢ ヨ ᩱ ࡛ ࡣ 」 ྜ య ࡟ ⏤ ᮶ ࡍ ࡿ
NOEࡀ ほࡀほࡉ ࢀ ࡞ ࠿ ࡗ ࡓ 㸬 㠀 ኚ ᛶ ᮲ ௳ ࡢ 㟁 Ẽ Ὃ ື ࡟ ࠾ ࠸ ࡚ ࡶ Mg 2+ 㠀 Ꮡ ᅾ ୗ ࡛ ࡣ 」 ྜ యࡉ ࢀ ࡎ 㸪 Ᏻ ᐃ ࡞ 」 ྜ య ࡢ ᙧ ᡂ ࡟ ࡣ Mg 2+ ࡀ ᚲ せ ࡛ ࠶ ࡗ ࡓ 㸬⌧ᅾࡣ㸪ṧᇶ≉␗ⓗᏳᐃྠ఩యᶆ㆑࡟ࡼࡗ࡚」ྜయ࡟⏤᮶ࡍࡿࢩࢢࢼࣝࡢᖐᒓࡢ☜ㄆ 㸪 ࠾ ࡼ ࡧ MDࢩ ࣑ ࣗ ࣞ ࣮ ࢩ ࣙ ࣥ ࡟ ࡼ ࡿ 」 ྜ య ࡢ Ᏻ ᐃ ᛶ ࡢ ゎ ᯒ ࢆ 㐍 ࡵ ࡚ ࠸ ࡿ 㸬

㻌

㻌

㻌

Fig. 3. Imino proton spectra of RNAs.㻌

㻌

㻌

㻌

㻌

Fig. 4. NOESY spectrum of the complex.

－ 263 －

P57

ᅛయNMRࢆ⏝࠸ࡓࣄࢺ⬻⏤᮶Aȕ42⥺⥔ࡢ◊✲࡟࠾ࡅࡿヨᩱࡢ᭱㐺໬࡜ᵓ㐀ゎᯒ‫ۑ‬ᑎぢ㡪㸪㔜ගెᇶ1㸪ᯇ⏣ຬ1㸪▼஭ె㄃1,2
1ᮾிᕤᴗ኱Ꮫ ⏕࿨⌮ᕤᏛ㝔
2⌮໬Ꮫ◊✲ᡤ BDR ඛ➃NMR㛤Ⓨ࣭ᛂ⏝◊✲ࢳ࣮࣒

Optimization of sample preparation and structural analysis in the research of brainderived Aȕ42 fibrils using solid-state NMR‫ۑ‬Hibiki Terami1, Yoshiki Shigemitsu1, Isamu Matsuda1, Yoshitaka Ishii1.2
1Department of Life Science and Technology, Tokyo Institute of Technology

2

Laboratory for Advanced NMR Application and Development, BDR, RIKEN
Alzheimer's disease (AD) is the most prominent form of dementia and has become a social problem as the

population ages. Misfolded amyloid-ȕ (Aȕ) peptides accumulated in a brain as senile plaques are considered
to be a primary cause of AD. The major isoforms of Aȕ in the brain affected by AD are 40-residue Aȕ40
and 42-residue Aȕ42, and Aȕ42 is considered to be more toxic than Aȕ40. In our group, we aim to compare
structures of Aȕ42 fibrils using the fibril fragments derived from minimal amount of several AD patients'
brain tissues as seeds by sensitivity-enhanced 1H-detecetd solid-state NMR. In this presentation, we conduct
experiments to optimize fibril extraction from brain tissue using animal brain tissue and synthetic Aȕ42 fibrils.
We will discuss possible structural changes of Aȕ42 fibrils during the extraction process and the optimizationof sample preparation methods, focusing on the structure of synthetic Aȕ42 fibrils.
࢔ࣝࢶࣁ࢖࣐࣮⑓(AD)ࡣㄆ▱⑕ࡢ୰࡛᭱ࡶ୺せ࡞⑌ᝈ࡛ࠊ㧗㱋໬࡟క࠸♫఍ၥ㢟࡟࡞ࡗ࡚࠸ࡿࠋ
࢔࣑ࣟ࢖ࢻ๓㥑యࢱࣥࣃࢡ㉁(APP)࠿ࡽ࢔࣑ࣟ࢖ࢻș(Aȕ)࣌ࣉࢳࢻࡀษࡾฟࡉࢀࠊ⥺⥔≧ࡢỿẊ࡜ࡋ࡚⬻ෆ࡟⵳✚ࡍࡿࡇ࡜ࡀⓎ⑕ࡢཎᅉࡢ୍ࡘ࡛࠶ࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿ1ࠋ⬻ෆ࡟ࡣ40ṧᇶࡢAȕ40࡜
42ṧᇶࡢAȕ42ࡀ୺࡞࢔࢖ࢯࣇ࢛࣮࣒࡜ࡋ࡚ᏑᅾࡋࠊAȕ42ࡣAȕ40࡜ẚ㍑ࡋ࡚จ㞟ࡋࡸࡍࡃ⚄⤒ẘᛶࡀᙉ࠸࡜ࡉࢀ࡚࠸ࡿ2ࠋ࣑ࢫࣇ࢛࣮ࣝࢹ࢕ࣥࢢࡋࡸࡍࡃ୙ᆒ୍࡞ᵓ㐀ࢆ࡜ࡾࡸࡍ࠸Aȕ42࡜ẚ㍑ࡋ
࡚ࠊAȕ40ࡣᐇ㦂ⓗ࡟ᢅ࠸ࡸࡍ࠸ࡓࡵඛ⾜ࡋ࡚⥺⥔ࡢ❧యᵓ㐀ゎᯒࡢ◊✲ࡀ㐍ࢇ࡛࠸ࡿࠋADᝈ⪅ࡢ⬻⤌⧊⏤᮶ࡢ࢔࣑ࣟ࢖ࢻ⥺⥔ࢆࢩ࣮ࢻ࡜ࡋ࡚Aȕ40⥺⥔ࢆఙ㛗ࡉࡏࡿ࡜ࠊᝈ⪅ࡈ࡜࡟␗࡞ࡿ❧యᵓ㐀ࢆ♧ࡍࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠸ࡿ3ࠋࡑࡢࡓࡵࠊ࢔࣑ࣟ࢖ࢻ⥺⥔ࡢ❧యᵓ㐀࡜ADࡢ⑕≧࡜ࡢ㛫࡟㛵ಀࡀ࠶ࡿ࠿࡝࠺࠿ὀ┠ࡉࢀ࡚࠸ࡿࠋࡲࡓࠊ᫖ᖺࠊᙜ◊✲ᐊ࡟࠾࠸࡚ࠊ⬻⤌⧊⏤᮶ࡢAȕ42⥺⥔ࡣin-vitro
࡛స〇ࡉࢀࡓAȕ42⥺⥔࡜␗࡞ࡿᵓ㐀ࢆྲྀࡿࡇ࡜ࡀ♧ࡉࢀࡓ4ࠋࡋ࠿ࡋࠊᝈ⪅࡟ࡼࡿAȕ42⥺⥔ࡢᵓ㐀ࡢ㐪࠸➼ࡣ᫂ࡽ࠿࡟࡞ࡗ࡚࠸࡞࠸ࠋ
ᙜ◊✲ᐊ࡛ࡣࠊ㧗ឤᗘࡢ1H᳨ฟᅛయNMRࢆ⏝࠸࡚」ᩘࡢADᝈ⪅ࡢࢧࣈࢢ࣒ࣛ㔞ࡢ᭱ᑠ㝈ࡢ⬻⤌⧊(0.1–0.2 g)࠿ࡽᚓࡓ࢔࣑ࣟ࢖ࢻ⥺⥔ࢆࢩ࣮ࢻ࡜ࡋ࡚Aȕ42⥺⥔ࢆస〇ࡋࠊࡑࡢ❧యᵓ㐀ࢆᝈ⪅ࡈ࡜࡟ẚ㍑ࡋࡼ࠺࡜ヨࡳ࡚࠸ࡿࠋᮏ◊✲࡛ࡣࠊື≀⬻⤌⧊࠾ࡼࡧ໬ᏛྜᡂࡋࡓAȕ42⥺⥔ࢆ⏝࠸࡚ࠊ⬻⤌⧊࠿ࡽࡢ࢔࣑ࣟ࢖ࢻ⥺⥔ᢳฟࡢ᭱㐺໬ࢆヨࡳࡓࠋྜᡂAȕ42⥺⥔ࡢᵓ㐀࡟╔┠ࡋࠊ⬻⤌⧊࠿ࡽࡢᢳฟ㐣⛬࡟࠾ࡅࡿAȕ42⥺⥔ࡢ❧యᵓ㐀ࡢኚ໬࠾ࡼࡧ⥺⥔ࡢᢳฟ᪉ἲࡢ᭱㐺໬࡟ࡘ࠸࡚㆟ㄽࡍࡿࠋ࢔࣑ࣟ࢖ࢻș㸪ᅛయNMR‫ࡁࡧࡦࡳࡽ࡚ۑ‬㸪ࡋࡆࡳࡘࡼࡋࡁ㸪ࡲࡘࡔ࠸ࡉࡴ㸪࠸ࡋ࠸ࡼࡋࡓ࠿

－ 264 － ᮏ◊✲࡟࠾ࡅࡿᐇ㦂࡟ࡣࠊ㣗⏝࡜ࡋ࡚ᕷ㈍ࡉࢀ࡚࠸ࡿ㇜ࡢ⬻ࢆ⏝࠸ࡓࠋࡍࡾࡘࡪࡋࡓ⬻⤌⧊࡟໬ᏛྜᡂࡋࡓAȕ42⥺⥔ࡢᠱ⃮ᾮࢆຍ࠼ࠊ᪤ሗ࡟ᚑ࠸5࢔࣑ࣟ࢖ࢻ⥺⥔ࡢᢳฟᐇ㦂ࢆ⾜ࡗࡓࠋྜᡂ
Aȕ42⥺⥔ࡢධࡗࡓ⬻⤌⧊࠿ࡽࠊࢫࢡ࣮ࣟࢫ⁐ᾮ୰࡛ࡢ㐲ᚰศ㞳ࠊDNase࠾ࡼࡧcollagenase࡟ࡼࡿศゎࠊ࠾ࡼࡧࠊ1% SDS࡟ࡼࡿฎ⌮ࢆ⤒࡚amyloid-rich࡞ᢳฟ≀ࢆᚓࡓࠋᚓࡽࢀࡓᢳฟ≀ࢆࢩ࣮ࢻ࡜ࡋ
࡚Aȕ42ࣔࣀ࣐࣮⁐ᾮ࡟ຍ࠼࡚࢖࣮ࣥ࢟ࣗ࣋ࢩࣙࣥࡋࠊ “brain-seeded” Aȕ42⥺⥔ࢆస〇ࡋࡓࠋࡇࡢ
㝿ࠊ⺯ගⰍ⣲thioflavin T (ThT)⏝࠸࡚⥺⥔ᙧᡂࡢ㐣⛬ࢆ㏣㊧ࡋࡓࠋᙜ᪥ࡢⓎ⾲࡛ࡣࠊᐇ㦂ࡢ᭱ึ࡟ຍ࠼࡚࠸ࡿ໬ᏛྜᡂAȕ42⥺⥔࠾ࡼࡧ௒ᅇࡢᐇ㦂࡛స〇ࡋࡓ “brain-seeded” Aȕ42⥺⥔ࢆࡑࢀࡒࢀᅛయNMR 2D 13C-13C ᐃ࠿ࡽᚓࡽࢀࡓࢫ࣌ࢡࢺࣝࢆẚ㍑ࡍࡿࡇ࡜࡛ࠊᢳฟ㐣⛬࡟࠾ࡅࡿ⥺⥔ࡢ❧యᵓ㐀ኚ໬࡟ࡘ࠸࡚㆟ㄽࡍࡿணᐃ࡛࠶ࡿࠋ

[References](1) Hardy & Higgins. (1992). Alzheimer’s Disease: The Amyloid Cascade Hypothesis. Science, 256,184í185.
(2) Burdick et al. (1997). Preferential adsorption, internalization and resistance to degradation of the
major isoform of the Alzheimer’s amyloid peptide, Aȕ1-42, in differentiated PC12 cells. BrainRes., 746, 275í284.
(3) Lu et al. (2013). Molecular Structure of ȕ-Amyloid Fibrils in Alzheimer’s Disease Brain Tissue.
Cell, 154, 1257í1268.
(4) Wickramasinghe et al. (2021). Sensitivity-Enhanced Solid-State NMR Detection of Structural
Differences and Unique Polymorphs in Pico- to Nanomolar Amounts of Brain-Derived andSynthetic 42-Residue Amyloidဩȕ Fibrils. J. Am. Chem. Soc., 143, 11462í11472.
(5) Scherpelz et al. (2016). Preparation of Amyloid Fibrils Seeded from Brain and Meninges. Methods

Mol. Biol., 1345, 299í312.

－ 265 －

P58

ᣢ⥆ྍ⬟࡞㧗ศᏊᮦᩱタィࢆᣦྥࡋࡓ105グ㏙Ꮚᢳฟ‫ۑ‬໭ᒣ⩧▮ ࠊᶓᒣ኱⛥ࠊᆤ஭⿱⌮ࠊ⳥ᆅ῟
ᶓ὾ᕷ❧኱Ꮫ኱Ꮫ㝔 ⏕࿨་⛉Ꮫ◊✲⛉⌮໬Ꮫ◊✲ᡤ ⎔ቃ㈨※⛉Ꮫ◊✲ࢭࣥࢱ࣮ ⎔ቃ௦ㅰศᯒ◊✲ࢳ࣮࣒
ྡྂᒇ኱Ꮫ኱Ꮫ㝔 ⏕࿨㎰Ꮫ◊✲⛉

NMR descriptor extraction oriented to sustainable polymer material design‫ۑ‬Syoya Kitayama1, Daiki Yokoyama2, Yuuri Tsuboi2, Jun Kikuchi1,2,3
1 Graduate School of Medical Life Science, Yokohama City University
2 RIKEN Center for Sustainable Resource Science
3 Graduate School of Bioagricultural Sciences, Nagoya University
The commercial products we use in our daily lives have a wide variety of polymer materials, and it isessential to understand their physical and chemical properties to design confortable usage in human society.
In this study, we attempted to extract relationships between physical properties and time-domain (TD)NMR relaxation curve data of multiple kinds of polymer materials. The relaxation curves and their PCA
showed the large variation of the strength in the initial stages of relaxation time within across polymer
types, suggesting that polymer structure and chemical properties affected physical properties.

࠙⫼ᬒࠚ㏆ᖺࠊ᪥ᖖ⏕ά࡛኱㔞࡟౑⏝ࡉࢀ࡚࠸ࡿ㧗ศᏊᮦᩱࡢ㈨※ᚠ⎔ࢆಁ㐍ࡋ⎔ቃ㈇Ⲵࢆᑠࡉࡃࡍࡿ
ືࡁࡀᙉࡲࡗ࡚࠸ࡿࠋᡃࠎࡀᬑẁ฼⏝ࡍࡿ㧗ศᏊᮦᩱ࡟ࡣࠊከ✀ከᵝ࡞⣲ᮦࡀ౑ࢃࢀ࡚࠾ࡾࠊࡇ
ࢀࡽࢆ♫఍࡛࠺ࡲࡃά⏝ࡋ࡚࠸ࡃࡓࡵ࡟ࡣࠊྛ⣲ᮦࡢ≀⌮࣭໬Ꮫⓗ≉ᛶࢆᢕᥱࡍࡿࡇ࡜ࡀᚲ㡲࡛࠶ࡿࠋࡇ࠺ࡋࡓከ✀ከᵝ࡞⣲ᮦࢆホ౯ࡍࡿࡓࡵ࡟ࡣࠊపࢥࢫࢺ࡛⣲ᮦࡢ≉ᛶࢆศᯒ࡛ࡁࡿᶵჾࢆ
⏝࠸࡚኱㔞ࡢࢹ࣮ࢱࢆ࢖ࣥࣇ࢛࣐ࢸ࢕ࢡࢫⓗᡭἲ࡛ᢅ࠺ᚲせࡀ࠶ࡿࠋప☢ሙ NMR ࡢ୍✀࡛࠶ࡿ༟ୖᆺ TD-NMR ࡣࠊ㧗☢ሙ NMR ࡟ẚ࡭タ⨨ࡸ⥔ᣢ࡟࠿࠿ࡿ㈝⏝ࡀᏳ౯࡛࠶ࡾࠊィ࡟࠿࠿ࡿ᫬㛫ࡸ‽ഛ࡞࡝ࡢࢥࢫࢺࡀప࠸࣓ࣜࢵࢺࡀ࠶ࡾࠊ኱㔞ࡢヨᩱࡢ≀ᛶ᝟ሗࢆྲྀᚓ࡛ࡁࡿࠋTD-NMRィࡣヨᩱࡢ⦆࿴᭤⥺ࢆィࡍࡿࡇ࡜࡛ࠊ⣲ᮦࡈ࡜ࡢ⦆࿴᫬㛫ࡢᕪ␗࡟ࡼࡗ࡚ᑐ㇟ࡢᅛࡉ➼ࡢ≀ᛶ᝟ሗࢆホ౯ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡉࡽ࡟ DQ/MAPE/SE/CPMG ࡢ␗࡞ࡿࣃࣝࢫࣉࣟࢢ࣒࡛ࣛࠊࢲ
࢖ࢼ࣑ࢵࢡࣞࣥࢪࡢ኱ࡁ࡞ືⓗ᝟ሗࢆᢳฟ࡛ࡁࡿ[1]ࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊከ✀㢮ࡢ㧗ศᏊᮦᩱࢆ
ヨᩱ࡜ࡋ TD-NMR ࡢ⦆࿴᭤⥺ࡢࢹ࣮ࢱࢆ⏝࠸࡚ࠊ≀ᛶ᝟ሗ࡜ᮦᩱ⣲ᮦ࡜ࡢ㛵㐃ࡢᢳฟࢆヨࡳ
ࡓࠋ
࠙᪉ἲࠚ
ヨᩱ࡟ࡣࠊ⤌ᡂࡸ〇㐀᮲௳ࡢ␗࡞ࡿ 424 ࢧࣥࣉࣝࡢ㧗ศᏊᮦᩱࢆ⏝࠸ࡓࠋ⣲ᮦࡢ≉ᛶࢆࡲ࡜ࡵ࡚ホ౯ࡍࡿࡓࡵ࡟ࠊ7 ✀ࡢ⏕ศゎ࣏࣐࣮ࣜࠊྜᡂᶞ⬡ࠊࢦ࣒࡟ศ㢮ࡋࡓࠋ⏕ศゎᛶ࣏࣐࣮ࣜࡢ୰࡛
ࡶ≉࡟ PLA ࡜ PVA ࡣ⤖ᬗ໬ᗘࡢࣂ࢚࣮ࣜࢩࣙࣥࡀ኱ࡁ࠸ࠋࡲࡓࠊྜᡂᶞ⬡ࠊࢦ࣒࡟ࡘ࠸࡚ࡣ␗
࡞ࡿ⤌ᡂࢆᣢࡘ」ᩘ✀㢮ࡢ㧗ศᏊヨᩱࡀྵࡲࢀ࡚࠸ࡿࠋィࡣ solid-echo ἲࢆ⏝࠸࡚⾜࠸ࠊྲྀᚓࡋࡓ⦆࿴᭤⥺ࢆ 0.00016 msec ࡈ࡜࡟ࣅࣥ໬ࡋ࡚ࡑࡢᙉᗘ᝟ሗ࡛ PCA ࢆ⾜ࡗࡓࠋ᫬㛫㡿ᇦNMRࠊᵓ㐀≀ᛶ┦㛵ࠊࢧ࣮࣮࢚࢟ࣗࣛࢥࣀ࣑࣮
‫ࢇࡹࡌࡕࡃࡁࠊࡾ࠺ࡺ࠸ࡰࡘࠊࡁ࠸ࡔࡲࡸࡇࡼࠊࡸ࠺ࡻࡋࡲࡸࡓࡁۑ‬－ 266 －

Figure. 1 (A) Relaxation curves of biodegradable polymers, resins, and rubbers, (B) PC1 and PC2 plots
highlighted by different materials, (C) Loading of PC1 and PC2.
࠙⤖ᯝ࡜⪃ᐹࠚ
ྲྀᚓࡋࡓ⦆࿴᭤⥺ࠊ࠾ࡼࡧࡑࡢ PCA ࡢ⤖ᯝࢆ⣲ᮦ࢝ࢸࢦࣜࡈ࡜࡟ᅗ♧ࡋࡓ(Fig. 1)ࠋPC1 ࡢᐤ୚⋡ࡣ 87.5%࡜㧗ࡃࠊLoading ᅗࡼࡾ⦆࿴ึᮇẁ㝵(~0.02 msec)ࡢᙉᗘࡀ PC㸯㍈ࡢኚື࡟኱ࡁࡃᐤ
୚ࡋ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡗࡓࠋ⦆࿴᭤⥺ࢆ☜ㄆࡋࡓ࡜ࡇࢁ⦆࿴ึᮇẁ㝵ࡢᙉᗘࡢࡤࡽࡘࡁࡀ኱ࡁ
ࡃࠊ⦆࿴ึᮇẁ㝵ࡢᙉᗘࡀྛ㧗ศᏊ⣲ᮦࡢ≉ᚩࢆ኱ࡁࡃ཯ᫎࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
PCA ࣉࣟࢵࢺࢆぢࡿ࡜࠾࠾ࡲ࠿࡟⣲ᮦࡈ࡜࡟ࡲ࡜ࡲࡗࡓศᕸࢆᣢࡗ࡚࠸ࡿࡓࡵࠊᮦᩱ⣲ᮦ࡜≀ᛶ᝟ሗ࡜ࡢ㛫࡟ࡣ㛵㐃ᛶࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡓࠋࡑࡢ୰࡛ࡶ࡜ࡾࢃࡅ PLAࠊPVAࠊྜᡂᶞ⬡ࡢࣉࣟࢵࢺୖࡢࡤࡽࡘࡁࡀ኱ࡁ࠿ࡗࡓࠋPLA ࡜ PVA ࡟ࡘ࠸࡚ࡣ⤖ᬗ໬ᗘࡢ኱ᖜ࡟␗࡞ࡿヨᩱࢆ౑⏝ࡋ࡚࠾ࡾࠊ⤖ᬗ໬ᗘ࡟ᛂࡌ࡚ศᏊ㛫ࡢ⤖ྜຊࡸᅛࡉࡢ㐪࠸ࡀ⏕ࡌࡓ⤖ᯝࠊྠࡌ⣲ᮦෆ࡛ࡶ⦆࿴᭤
⥺ࡢࡤࡽࡘࡁࡀ⏕ࡌࡓ࡜⪃࠼ࡽࢀࡓࠋࡲࡓࠊྜᡂᶞ⬡࡜ศ㢮ࡋࡓ୰࡟ࡣከ✀㢮ࡢ⣲ᮦࢆྵࢇ࡛࠸
ࡿࡓࡵࠊ⦆࿴᭤⥺࡟㐪࠸ࡀ⏕ࡌࡓ࡜ᛮࢃࢀࡿࠋ୍᪉࡛ࠊࢦ࣒ࡣከ✀㢮ࡢ⣲ᮦࢆྵࢇ࡛࠸ࡿ࡟ࡶ㛵ࢃࡽࡎ⦆࿴᭤⥺࡟኱ࡁ࡞㐪࠸ࡣぢࡽࢀ࡞࠿ࡗࡓࡇ࡜࠿ࡽࠊ≀ᛶ࡟ඹ㏻Ⅼࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ௨
ୖ࠿ࡽࠊᮦᩱ⣲ᮦࡀヨᩱࡢ≀ᛶ࡟㛵୚ࡋ࡚࠾ࡾࠊྠ⣲ᮦ࡛ࡶ〇㐀㐣⛬ࡢ㐪࠸࡛␗࡞ࡿ≀ᛶࢆᣢࡘሙྜࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡓࠋ
௒ᚋࡣ௒ᅇᐃࡋࡓ≀ᛶ᝟ሗࡔࡅ࡛࡞ࡃࠊᅛయ NMR ࡸ IR ࡜࠸ࡗࡓከᵝ࡞ᶵჾࢆ⏝࠸࡚ᚓࡽࢀࡿ᝟ሗ࡜ࡢ㛵㐃ࢆᢳฟࡍࡿࡇ࡜࡛ࠊᮦᩱ⣲ᮦࡢ≀ᛶࡸ໬Ꮫᵓ㐀࡜ࡢ㛵㐃࡟ࡘ࠸࡚ࡢ⌮ゎࢆ῝ࡵ࡚࠸ࡁࡓ࠸࡜⪃࠼࡚࠸ࡿࠋ
References[1] Hara, K., Yamada, S., Kurotani, A., Chikayama, E. and Kikuchi, J. “Materials informatics approach using
domain modelling for exploring structure-property relationships of polymers” Sci. Rep. 12, 10558 (2022).

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P59

NMR࡟ࡼࡿ㛢㙐ᚠ⎔ᘧ㝣ୖ㣴Ṫ㨶ࡢ௦ㅰ࣭⫗㉁ศᯒ
‫୸ۑ‬ᶫឡ⨾1㸪ᶓᒣ኱⛥3㸪ᆏ⏣◊஧3㸪ᑎᒣ្1,2㸪⳥ᆅ῟2,3,4
1ᶓ὾ᕷ❧኱Ꮫ⌮Ꮫ㒊⏕࿨་⛉Ꮫ⛉
2 ԥශࢤཱི୉ָ୉ָӅਫ਼ໍҫՌָ‫ڂݜ‬Ռ        

3 ཀྵԿָ‫ݱࣁڧ؂ॶڂݜ‬Ռָ‫ڂݜ‬ιϱνʖ        

4 ໌‫ݻ‬Բ୉ָ୉ָӅਫ਼ໍ೸ָ‫ڂݜ‬Ռ

Metabolism and meat quality analysis of closed circulation land-based fish by NMR‫ۑ‬Aimi Maruhashi1, Daiki Yokoyama3, Kenji Sakata3, Kei Terayama2, Jun Kikuchi2,3,4
1

Department of Medical Life Science, Yokohama City University

2 Graduate School of Medial Life Science, Yokohama City University
3 RIKEN Center for Sustainable Resource Science4

Graduate School of Bioagricultural Sciences, Nagoya university

The denitrification process is a key metabolic factor for water circulation systems in land-based
aquaculture. We analyzed the impact of Poly butylene succinate-co-butylene adipate (PBSA) filter media
toward fish metabolism and fish meat quality using NMR, comparing the fecal and muscle metabolome of
Epinephelus coioides between the tanks equipped with commercial filter media and those with PBSA filter
media.
ࣉࣛࢿࢱ࣮࣭ࣜࣂ࢘ࣥࢲ࣮ࣜࡣே㢮ࡀ⏕Ꮡ࡛ࡁࡿᏳ඲࡞άື㡿ᇦ࡜ࡑࡢ㝈⏺Ⅼࢆᐃ⩏ࡍࡿᣦᶆ࡛
࠶ࡿࠋ9 㡯┠ࡢ࠺ࡕࠊ❅⣲ࡸࣜࣥ᤼ฟࢆ୺࡜ࡍࡿ⏕≀ᆅ⌫໬Ꮫⓗᚠ⎔࠾ࡼࡧ⏕≀ከᵝᛶࡢపୗࡀ
㝈⏺Ⅼࢆ㉸㉺ࡋ࡚࠾ࡾࠊᐩᰤ㣴໬ࡸ⏕ែ⣔◚ቯ࡞࡝ࡢ⎔ቃ㈇Ⲵ࡟ᙉࡃ㛵㐃ࡋ࡚࠸ࡿࠋ
㛢㙐ᚠ⎔ᘧ㝣ୖ㣴Ṫࡣ㣫⫱Ỉࡀᾏ࡬᤼ฟࡉࢀ࡞࠸Ⅼ࠿ࡽᐩᰤ㣴໬㜵Ṇ࡟⧅ࡀࡾࠊ⏕ែ⣔ಖ඲ࡸ⎔ቃၥ㢟ゎỴࡢ⣒ཱྀ࡜࡞ࡾᚓࡿࠋࡓࡔࡋࠊ㨶࠿ࡽ᤼ฟࡉࢀࡿ❅⣲໬ྜ≀ࡢỈᵴෆ⵳✚ࡀᦤ㣵⋡ࡸ㣴Ṫຠ⋡పୗࡢせᅉ࡜࡞ࡿࡓࡵࠊ⬺❅ฎ⌮ࡀᚲせ࡜࡞ࡿࠋ⏕ศゎᛶ࣏࣐࣮࡛ࣜ࠶ࡿ࣏ࣜࣈࢳࣞࣥࢧ
ࢡࢩࢿ࣮ࢺ࢔ࢪ࣮࣌ࢺ PBSA ࢁᮦࡣࠊ௜╔ᚤ⏕≀ࡢ⬺❅࡟ࡼࡿ㣫⫱⎔ቃᨵၿࡀᣦ᦬ࡉࢀ࡚࠸ࡿࡶ
ࡢࡢࠊ㨶௦ㅰᶵᵓ࡬ࡢᙳ㡪ࡣ୙࡛᫂࠶ࡿࠋࡑࡇ࡛ᮏ◊✲ࡣࠊᕷ㈍ࢁᮦỈᵴ࠾ࡼࡧ PBSA ࢁᮦỈᵴෆ࡛㧗௜ຍ౯್㨶✀࡛࠶ࡿࢳࣕ࢖࣐ࣟࣝࣁࢱࡢ㣫⫱ࢆ⾜࠸ࠊ㨶௦ㅰ≀ࡢ֦झ NMR ‫ܯ‬଎ 2DJresTD-NMR ࠿ࡽࠊPBSA ࢁᮦࡀ㨶௦ㅰࡸ⫗㉁࡬୚࠼ࡿᙳ㡪ࢆ᫂ࡽ࠿࡟ࡋࡓࠋ
2ࡘࡢỈᵴ ᕷ㈍ࢁᮦ ࢚࣮ࣁ࢖࣒♫ࢧࣈࢫࢺࣛࢵࢺࣉࣟ ỈᵴࠊPBSAࢁᮦỈᵴ ࢆ⏝ពࡋࠊ2020ᖺ9᭶࠿ࡽ2021ᖺ10᭶ࡲ࡛ྛỈᵴ150༉ࡎࡘ㣫⫱ࢆ⾜ࡗࡓࠋ㣫⫱Ỉᵴࡢ᫬⣔ิỈࢧࣥࣉࣝࡢỈ㉁ศ
ᯒࢆ⾜ࡗࡓ࡜ࡇࢁࠊPBSAࢁᮦỈᵴ࡛ࡣ❅⣲⃰ᗘࡀపࡃ⥔ᣢࡉࢀࡓࡇ࡜࠿ࡽࠊPBSAࢁᮦỈᵴ࡛ࡣ⬺❅ࡀಁ㐍ࡉࢀ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ
ḟ࡟ࠊ㨶௦ㅰ≀࡛࠶ࡿ⣅౽࠾ࡼࡧ㨶⫗ࡢNMRࢫ࣌ࢡࢺࣝ(2DJ-res)ࢆ⏝࠸ࡓ௦ㅰࣉࣟࣇ࢓࢖ࣜࣥ
ࢢࢆ㐙⾜ࡋࡓ࡜ࡇࢁࠊ⣅౽୺ᡂศศᯒ࡛ࡣỈᵴ㛫࡛㢧ⴭ࡞ᕪࡀ࡞࠿ࡗࡓࡢ࡟ᑐࡋࠊ㨶⫗୺ᡂศศ
ᯒ࡛ࡣᕷ㈍ࢁᮦỈᵴࡢ㣫⫱ᚋᮇ 3᭶௨㝆 ࡟PC2ࡀ㈇ࡢ᪉ྥ࡟೫ࡗ࡚࠸ࡓ Fig.1 ࠋᕷ㈍ࢁᮦỈᵴ࡛ࡣ㣫⫱Ỉ୰ࡢ◪㓟⵳✚࡟ࡼࡗ࡚pHࡀ⮴Ṛ㝈⏺௜㏆ࡲ࡛పୗࡋࡓࡓࡵ࡟Ṛஸಶయᩘࡀᛴቑࡋ࡚
࠾ࡾࠊࡇࡢPC2ୖࡢኚ໬ࡣࡇ࠺ࡋࡓ⎔ቃࢫࢺࣞࢫ࡟ࡼࡗ࡚㨶ࡢ௦ㅰࡀኚ໬ࡋࡓࡇ࡜࡟㉳ᅉࡍࡿ࡜
㝣ୖ㣴Ṫ㸪❅⣲ᚠ⎔㸪௦ㅰࣉࣟࣇ࢓࢖ࣜࣥࢢ
‫ࡳ࠸࠶ࡋࡣࡿࡲۑ‬㸪ࡼࡇࡸࡲࡔ࠸ࡁ㸪ࡉ࠿ࡓࡅࢇࡌ㸪࡚ࡽࡸࡲࡅ࠸㸪ࡁࡃࡕࡌࡹࢇ

－ 268 －

⪃࠼ࡽࢀࡿࠋ

CFࡲࡓࠊ┠ⓗኚᩘࢆ㨶⫗୺ᡂศศᯒࡢ
PC2ࠊㄝ᫂ኚᩘࢆ⫧‶ᗘࠊỈᵴࠊ㣫⫱ᮇ㛫࡜ࡋ࡚㔜ᅇᖐศᯒࢆᐇ᪋ࡋࡓ࡜ࡇ
ࢁࠊ⫧‶ᗘࡀ㧗ࡃPBSAࢁᮦࢆ౑⏝ࡍtankࡿ࡯࡝PC2ࡀࣉࣛࢫ࡟೫ࡿࡇ࡜ࡀุ᫂

commercialࡋࡓࠋࡉࡽ࡟ࠊ㨶⫗୺ᡂศศᯒࡢᅉᏊ

PBSA㈇Ⲵ㔞ࡢ⤖ᯝ࠿ࡽࠊPBSAࢁᮦỈᵴࡢ㨶⫗࡟ࡣ᪨࿡ᡂศ࡛࠶ࡿ࢖ࣀࢩࣥ㓟day

IMP ࠊGlycineࡸThreonineࡀከࡃྵࡲ

60days90daysࢀ࡚࠸ࡓࡇ࡜࠿ࡽࠊPBSAࢁᮦฎ⌮࡟

150daysࡼࡾ㨶⫗ࡢ⫗㉁ࡀྥୖࡍࡿྍ⬟ᛶࡀ

240days࠶ࡿ࡜⪃ᐹࡋࡓࠋ
ࡲࡓࠊ≀ᛶホ౯ࢆ⾜࠺ࡓࡵ࡟ࠊTDNMR (CPMGἲ)࡟ࡼࡿࢫࣆࣥࢫࣆࣥ
⦆࿴᫬㛫(T2)ࡢ

ᐃࢆ⾜ࡗࡓࠋT2ࡣศᏊࡢࣈࣛ࢘ࣥ㐠ືࡸ⤖ྜࡢᅇ㌿ࢆ཯

330daysFig. 1. Principal component analysis of fish muscle
metabolome.

7UDQVLWLRQFXUYHᫎࡋ࡚࠸ࡿࡓࡵࠊ㨶⫗ࡢ◳ࡉࡸỈศ≧ែࡢホ౯ࡀྍ⬟࡛࠶ࡿࠋணഛヨ㦂࡜ࡋ࡚ࢳࣕ࢖࣐ࣟࣝࣁࢱ࠾ࡼࡧࢪࣕ࢖࢔

)LWWLQJʤVXPPDWLRQʥ)LUVWILWWLQJFRPSRQHQWࣥࢺࣁࢱ㨶⫗ࢆ⏝࠸࡚⦆࿴᭤⥺ࢆྲྀᚓࡋᡂศศ㞳ࢆ⾜ࡗࡓ࡜ࡇࢁࠊ⦆࿴ࡢ
▷࠸⤖ྜỈࡢᡂศ(➨1ࣇ࢕ࢵࢸ࢕ࣥࢢ

6HFRQGILWWLQJFRPSRQHQWᡂศ)࡜⦆࿴ࡢ㛗࠸⮬⏤Ỉᡂศ(➨2ࣇ࢕ࢵࢸ࢕ࣥࢢᡂศ)࡟ศ㞳ࡍࡿࡇ࡜࡛ࠊ
➽⤌⧊୰ࡢ⤖ྜỈ࡜⮬⏤Ỉࡢẚ⋡ࢆィ⟬ࡍࡿࡇ࡜ࡀ࡛ࡁࡓ(Fig. 2)ࠋ௚࡟ࡶ
DQ/MAPE/SEࡸT1- T2┦㛵࡜࠸ࡗࡓࣃ
ࣝࢫࣉࣟࢢ࣒ࣛࢆ㐺⏝ࡍࡿࡇ࡜࡛ࠊ
PBSAࢁᮦฎ⌮࡟ࡼࡿ㨶⫗㉁࡬ࡢᙳ㡪
















7UHOD[DWLRQࢆ᳨ドࡋࠊࡉࡽ࡟໬Ꮫ⤌ᡂ᝟ሗ➼࡜ࡢ

Fig. 2. Measurement of T2 relaxation time curve of㛵ಀᛶࢆከゅⓗ࡟㆟ㄽࡋ࡚࠸ࡃணᐃ

fish muscle metabolome by TD-NMR.

࡛࠶ࡿࠋ
References(1) Mekuchi,M. Sakata,K. Yamaguchi,T. Koiso,M. Kikuchi,J. (2017) Trans-omics approaches used tocharacterise fish nutrional biorhythms in leopard coral grouper (Plectropomus leopardus). Sci Rep. 7, 9372
(2) Wei,F. Ito,K. Sakata,K. Asakura,T. Date,Y. Kikuchi,J. (2021) Fish ecotyping based on machine learningand inferred network analysis of chemical and physical properties. Sci Rep. 11, 3766
(3) Date,Y. Wei,F. Tsuboi,Y. Ito,K. Sakata,K. Kikuchi,J. (2021) Relaxometric learning: a pattern recognition
method fot T2 relaxation curves based on machine learning supported by an analytical framework. BMC
Chemistry 15,13－ 269 －

P60

࢔࣑ࣀ㓟ኚ␗࡜ᅽຊᦤືࢆ⏝࠸ࡓࢱࣥࣃࢡ㉁ࡢኚᛶ୰㛫యࡢᏳᐃ໬
‫ۑ‬໭ἑ๰୍㑻㸪ⱝᮏᣅᮁ2, ᒣᮏ⣧ஓ3, ᑠฟ᛭ዉ3, ໭ཎு11❧࿨㤋኱Ꮫ⸆Ꮫ㒊2❧࿨㤋኱Ꮫ㝔⏕࿨⛉Ꮫ㒊
3❧࿨㤋኱Ꮫ㝔⸆Ꮫ㒊

Amplification of the specific conformational fluctuation of proteins by site-specificmutagenesis and hydrostatic pressure: Outer Surface Protein A‫ۑ‬Soichiro Kitazawa1, Takuro Wakamoto2, Junya Yamamoto3, Reina Koide3, Ryo Kitahara1
1

College of Pharmaceutical Sciences, Ritsumeikan Univ. Japan

2

Graduate School of Life Science, Ritsumeikan Univ. Japan

3

Graduate School of Pharmacy, Ritsumeikan Univ. Japan
Conformational fluctuation is crucial to protein function. Outer surface protein A (OspA) is comprised of

N- and C-terminal globular domains linked by a central single-layer-E-strand. Solution nuclear magnetic
resonance (NMR) studies have shown that the central E-strand and C-terminal domain, containing receptorbinding site, are less stable than the N-terminal domain and partially disordered, indicating a presence of theintermediate state between the native folded state and completely unfolded state. In the previous study, wesuggested that partial disordering is advantageous for the receptor recognition because the binding site of
OspA is exposed to solvent. Herein we demonstrate that ampli¿cation of a speci¿c conformational Àuctuationby pressure perturbation and site-speci¿c mutagenesis. The salt-bridge-destabilized variant E160D and thecavity-enlarged variant I243A favored the intermediate. The proportion of the intermediate is almost 100%in E160D at 250 MPa. Strategies using a suitably chosen point mutation with high pressure are generally
applicable for amplification of specific conformational fluctuation and potentially improve our understandingof the high-Gibbs free energy conformations of proteins.
࠙⥴ゝࠚࢱࣥࣃࢡ㉁ࡣỈ⁐ᾮ୰࡛ᵓ㐀ゎᯒ࠿ࡽᚓࡽࢀࡿ᭱Ᏻᐃ࡞ኳ↛≧ែࡓࡔ୍ࡘࢆྲྀࡗ࡚࠸ࡿࢃࡅ࡛
ࡣ࡞ࡃࠊᵓ㐀ⓗ࡟ᦂࡽ࠸࡛࠾ࡾࠊࡑࡢᰂ㌾ᛶࡀᶵ⬟Ⓨ⌧࡟ᐤ୚ࡋ࡚࠸ࡿࠋOuter surface protein
A(OspA)ࡣNᮎ➃ഃ࡜Cᮎ➃ഃࡢ⌫≧ࢻ࣓࢖ࣥࡀsingle-layer- E-strand࡟ࡼࡾ⧅ࡀࢀࢱࣥࢹ࣒ᵓ㐀ࢆ
ᙧᡂࡋࡓ31 kDaࡢࢱࣥࣃࢡ㉁࡛࠶ࡿࠋOspAࡢ୰ኸE-strand㡿ᇦ࠿ࡽࡑࡢཷᐜయㄆ㆑㒊఩ࡀᏑᅾࡍ
ࡿCᮎ➃ഃࢻ࣓࢖ࣥࡲ࡛ࡣNᮎ➃ࢻ࣓࢖ࣥ࡜ẚ㍑ࡍࡿ࡜ᵓ㐀Ᏻᐃᛶࡀప࠸ࡇ࡜ࡀỈ⣲/㔜Ỉ⣲(H/D)஺᥮NMRᐇ㦂ࡸ㧗ᅽNMRᐇ㦂࡞࡝ࡢ◊✲࠿ࡽࢃ࠿ࡗ࡚࠸ࡿࠋࡇࡢ㡿ᇦࡀኚᛶࡋࡓᒁᡤኚᛶ≧ែࡣࠊࡑࡢኚᛶ࡟క࠸ཷᐜయㄆ㆑㒊఩ࡀ㟢ฟࡋࠊཷᐜయ᥈⣴✵㛫ࡀቑຍࡍࡿࡇ࡜࠿ࡽཷᐜయㄆ㆑࡟࡜ࡗ࡚㔜せ࡞≧ែ࡛࠶ࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿ1ࠋࡋ࠿ࡋࠊࡇࡢᒁᡤኚᛶ≧ែࡣศᕸ⋡ࡀᑠࡉ࠸ࡇ࡜࠿ࡽほ ࡍࡿࡇ࡜ࡣᅔ㞴࡛࠶ࡾࠊࡑࡢ❧యᵓ㐀ࡸᵓ㐀ᦂࡽࡂࡢไᚚᶵᵓࡢゎ᫂ࡣᅔ㞴࡛࠶ࡿࠋࡑ
ࡇ࡛ᡃࠎࡣCᮎ➃ཬࡧ୰ኸ㡿ᇦࡢᏳᐃᛶ࡟㔜せ࡞࢔࣑ࣀ㓟ṧᇶࢆኚ␗ࡉࡏࡿࡇ࡜࡟ࡼࡾᒁᡤኚᛶ
≧ែࢆᶍೌࡋࡓኚ␗యࡢస〇ࢆヨࡳࡓ2ࠋ㧗ᅽຊNMR ᒁᡤኚᛶ≧ែ 㧗࢚ࢿࣝࢠ࣮≧ែ‫࠺ࢁࡕ࠸࠺ࡑࢃࡊࡓࡁۑ‬, ࢃ࠿ࡶ࡜ࡓࡃࢁ࠺, ࡸࡲࡶ࡜ࡌࡹࢇࡸ, ࡇ࠸࡛ࢀ࠸࡞, ࡁࡓࡣࡽࡾࡻ࠺

－ 270 －࠙᪉ἲࠚC ᮎ➃㡿ᇦ࠿ࡽ୰ኸ㡿ᇦࢆᏳᐃ໬ࡉࡏ࡚࠸ࡿ
K189-E160 㛫ࡢሷᶫࡢ┦஫స⏝ࢆῶᙅࡉࡏࡓኚ
␗య E160D ࢆస〇ࡋࡓࠋࡲࡓ C ᮎ➃ࢻ࣓࢖ࣥࡢ
✵㝽ࢆᣑᙇࡉࡏࡓኚ␗య I243A ࢆస〇ࡋࡓࠋ
H/D஺᥮ NMR ᐇ㦂ࠊ㧗ᅽຊ NMR ᐇ㦂ࠊ㧗ᅽຊࢺࣜࣉࢺࣇ࢓ࣥ⺯ගᐇ㦂࡟ࡼࡾࡑࡢᵓ㐀ཬࡧ⇕ຊᏛⓗᏳᐃᛶࢆホ౯ࡋࡓࠋ࠙⤖ᯝ࣭⪃ᐹࠚ 㧗ᅽࢺࣜࣉࢺࣇ࢓ࣥ⺯ගᐇ㦂࡟ࡼࡾ㔝⏕ᆺ࠾
Fig. 1. Pressure-induced changes in theࡼࡧᒁᡤኚᛶ≧ែᶍೌኚ␗య(E160D, I243A)ࡢ
maximum wavelength of fluorescence for WT*(‫)ە‬, E160D (‫)ڹ‬, and I243A (‫ )ڧ‬at 313 K.
Ᏻᐃᛶࢆぢ✚ࡶࡗࡓࠋOspA ࡢࢺࣜࣉࢺࣇ࢓ࣥࡣ
C ᮎ➃ᵓ㐀ࢻ࣓࢖ࣥഃ࡛࠶ࡿ 216 ṧᇶ࡟Ꮡᅾࡋࠊ
ࢱࣥࣃࢡ㉁୰࡟ᇙἐࡋ࡚࠸ࡿࠋࡑࡢࡓࡵ⺯ගࢫ࣌ࢡࢺࣝࡢኚ໬ࡣ C ᮎ➃ᵓ㐀ࢻ࣓࢖ࣥࡢ≧ែࢆᙉࡃ཯ᫎࡍࡿࠋ㔝⏕ᆺ࠾ࡼࡧኚ␗యࡢ⺯ගࢫ࣌ࢡࢺࣝࡢ᭱኱⺯ගἼ㛗ࡣຍᅽ࡟క࠸㧗Ἴ㛗ഃ࡬⛣ືࡋࡓ(Fig. 1)ࠋࡇࢀࡣ C ᮎ➃ࢻ࣓࢖ࣥࡀኚᛶࡋࢺࣜࣉࢺࣇ࢓ࣥࡀࣂࣝࢡỈ࡟㟢ฟࡋࡓࡇ࡜ࢆ♧၀ࡍࡿࠋኚ␗యࡣ㔝⏕ᆺ࡜ẚ㍑ࡍࡿ࡜᫂ࡽ࠿࡟పᅽ࡛᭱኱⺯ගἼ㛗ࡢኚ໬ࡀほ ࡉࢀ࡚࠾ࡾࠊC ᮎ➃ࢻ࣓࢖ࣥࡢᏳᐃᛶࡢపୗࡀ♧၀ࡉࢀࡓࠋࡇࡢ⤖ᯝ࠿ࡽᒁᡤኚᛶ≧ែࡢ'Gqࡣ 31 r 4 (WT), 17 r 3(E160D), 11 r 2 kJ/mol (I243A), 'Vqࡣ127 r 16 (WT), 130 r 20 (E160D), 100 r 20 mL/mol (I243A)
࡜ぢ✚ࡶࡿࡇ࡜ࡀ࡛ࡁࡓࠋE160D ࠾ࡼࡧ I243A ࡣࡑࢀࡒࢀ WT ࡟ẚ࡭ 200 ಸ (E160D)࡜ 2000
(I243A)ಸࡲ࡛ศᕸ⋡ࡀቑຍࡋࡓࠋሷᶫῶᙅኚ␗య E160D ࡢ㒊ศࣔࣝయ✚ࡣ࠾࠾ࡼࡑ㔝⏕ᆺ࡜୍⮴ࡋࡓࠋࡑࡢ୍᪉ࠊ✵㝽ᣑᙇኚ␗య I243A ࡣࠊண᝿࡜ࡣ␗࡞ࡾ㒊ศࣔࣝయ✚ࡀῶᑡࡋࡓࠋࡇࢀࡣ✵㝽࿘㎶ࡢ␯ỈᛶṧᇶࡢỈ࿴࡜෌㓄ิ࡟ࡼࡾࠊ✵㝽ࡢయ✚ࡀῶᑡࡋࡓᙳ㡪࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ 㧗ᅽຊNMRἲ࡟ࡼࡿE160Dࡢゎᯒࢆ⾜ࡗࡓ ࠋ E160D ኚ ␗ య ࡣE1-E7 ࡟ 㛵 ࡋ࡚ ࡣ 250
MPaࡲ࡛ࡢ⠊ᅖ࡛ಙྕᙉᗘࡢῶᑡࡣぢࡽࢀࡎ (Fig. 2A)ࠊ❧యᵓ㐀ࡀኳ↛≧ែᵝᵓ㐀࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋࡑࢀ࡟ᑐࡋ࡚E9-E21ࡢ
୰ኸ㡿ᇦ࠿ࡽCᮎ➃ࢻ࣓࢖ࣥࡣಙྕᙉᗘࡢῶᑡࡀぢࡽࢀ (Fig. 2C)ࠊࡑࢀ࡟క࠸ኚᛶಙྕࡀほࡉࢀࡓࠋࡑࢀࡽ࡟ᣳࡲࢀࡿE8㡿ᇦ࡟࠾࠸࡚ࡣ114࠿ࡽಙྕᙉᗘࡢῶᑡࡀほࡉࢀ࡚࠾ࡾ(Fig. 2B)ࠊ114࠿ࡽᒁᡤⓗ࡟ኚᛶFig. 2. Pressure-induced changes in the peakࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋE160Dኚ␗యࡣ200

intensity of OspA E160D variant. Peak intensities(volumes) in ȕ1íȕ7 (A), ȕ8 (B), and ȕ9íȕ21 (C),normalized to those at 0.1 MPa, were plotted as afunction of pressure. Open circles indicate averagevalues at different pressure conditions(C). (D)Mapping of residues onto the crystal structure (PDBID1OSP, blue, increasing peak intensity orunperturbed by pressure; red, losing intensity bypressure; gray, no data or peak-overlap).

MPa௨ୖ࡟࠾࠸࡚Cᮎ➃ࢻ࣓࢖ࣥࡢኳ↛≧ែࡢಙྕࡀ࡯࡜ࢇ࡝᏶඲࡟ᾘኻࡍࡿ (Fig.
2D)ࠋࡇࡢࡇ࡜࠿ࡽࠊ㔝⏕ᆺ࡛ࡣ250 MPa࡛
80%ࡔࡗࡓᒁᡤኚᛶ≧ែࡀE160Dኚ␗࡟ࡼ
ࡾ࡯ࡰ100%ࡲ࡛Ᏻᐃ໬ࡍࡿࡇ࡜࡟ᡂຌࡋ
ࡓࠋ
References[1] R. Kitahara et al. Biophys. J. 102, 916-926, 2012.

[2] Wakamoto et al. J. Phys. Chem. B 126, 1868-1875, 2022.

－ 271 －

P61ᑠ⬊య⭷㈏㏻⺮ⓑ㉁VAP-BཬࡧVAP-B-FFAT motif」ྜయࡢ
NMRᵓ㐀ゎᯒ‫ۑ‬ᡞᕝ⯟1ࠊྂᯈᜤᏊ2ࠊᑠᯘ┤ᏹ3ࠊ⸨ཎᩄ㐨2ࠊඣᔱ㛗ḟ㑻1,21ᶓ὾ᅜ❧኱Ꮫ኱Ꮫ㝔࣭⌮ᕤᏛᗓ
2኱㜰኱Ꮫ࣭⺮ⓑ㉁◊✲ᡤ3⌮໬Ꮫ◊✲ᡤ࣭ᨺᑕග⛉Ꮫ◊✲ࢭࣥࢱ࣮

NMR structural analysis of integral endoplasmic reticulum protein VAP-B and VAP-BFFAT motif complex‫ۑ‬Wataru Togawa1, Kyoko Furuita2, Naohiro Kobayashi3, Toshimichi Fujiwara2, Chojiro Kojima1,2
1 Graduate School of Engineering and Science, Yokohama National University
2 Institute for Protein Research, Osaka University
3 RIKEN, RIKEN Spring-8 Center

 VAMP-associated protein (VAP), which is a transmembrane protein mainly localized in the endoplasmic
reticulum, is involved in intracellular functions by interacting with various proteins located in the organelle
membrane or cell membrane. The major sperm protein (MSP) domain on the N-terminal side of VAP is themain interaction region. In mammals, there are two types of VAPs, VAP-A and VAP-B, and the T46I and
P56S mutations in the VAP-B MSP domain are thought to be associated with familial amyotrophic lateralsclerosis (fALS)2,3. Therefore, understanding the structure and dynamics of the VAP-B MSP domaincomparing to VAP-A is important in elucidating the mechanism of ALS onset and developing therapeutic
methods. In this study, we analyzed the three-dimensional structure of the human VAP-B MSP domain and
VAP-B-FFAT motif complex by using solution NMR.
࠙ࡣࡌࡵ࡟ࠚ
୺࡟ᑠ⬊య࡟ᒁᅾࡍࡿ⭷㈏㏻⺮ⓑ㉁࡛࠶ࡿ VAMP-Associated Protein㸦VAP) ࡣࠊ࢜ࣝ࢞ࢿࣛ⭷࠶ࡿ࠸ࡣ⣽⬊⭷ࡀ஫࠸࡟㏆᥋ࡋࡓ⭷᥋ゐ㡿ᇦ (MCS) ࡟࠾࠸࡚ࠊᵝࠎ࡞⺮ⓑ㉁࡜┦஫స⏝ࡍࡿࡇ࡜࡛⣽⬊ෆࡢᶵ⬟࡟㛵୚ࡋ࡚࠸ࡿࠋVAP ࡢ N ᮎ➃ഃ࡟࠶ࡿ Major Sperm Protein㸦MSP㸧ࢻ࣓࢖ࣥࡀ
୺࡞┦஫స⏝㡿ᇦ࡛࠶ࡾࠊFFAT motif ࡜࿧ࡤࢀࡿ࢔࣑ࣀ㓟㓄ิࢆྵࡴ⺮ⓑ㉁࡜⤖ྜࡍࡿࡇ࡜࡛⬡㉁㍺㏦ࡢ㊊ሙࡢᙧᡂࡸᜏᖖᛶࡢ⥔ᣢࡀ࡞ࡉࢀ࡚࠸ࡿࠋ1 ့ங㢮࡛ࡣ VAP-A ཬࡧ VAP-B ࡢ஧✀㢮ࡀᏑᅾࡍࡿࡀࠊVAP-B MSP ࢻ࣓࢖ࣥࡢ T46I ཬࡧ P56S ኚ␗ࡣᐙ᪘ᛶ➽ⴎ⦰ᛶഃ⣴◳໬⑕ (fALS)࡞
࡝ࡢ⚄⤒⑌ᝈ࡜㛵㐃ࡀ࠶ࡿ࡜⪃࠼ࡽࢀ࡚࠸ࡿࠋ2,3 ᚑࡗ࡚ࠊVAP-B MSP ࢻ࣓࢖ࣥࡢᵓ㐀ࡸࢲ࢖ࢼ࣑
ࢡࢫࠊ┦஫స⏝ᶵᵓࢆᢕᥱࡋࠊVAP-A ࡜ẚ㍑ࡋࡓ VAP-B ࡢᵓ㐀≉ᛶࡸ≉᭷ࡢศᏊᶵ⬟ࢆ⪃ᐹࡍࡿࡇ࡜ࡣ⚄⤒⑌ᝈⓎ⑕࣓࢝ࢽࢬ࣒ࡢゎ᫂ࡸ἞⒪ἲࡢ㛤Ⓨ࡟࠾ࡅࡿᇶ┙ⓗ▱㆑࡜ࡋ࡚㔜せ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋᮏ◊✲࡛ࡣ VAP-B ࡢᵓ㐀≉ᛶࡸ MCS ࡛ࡢ⬡㉁㍺㏦࡟࠾ࡅࡿ⺮ⓑ㉁㛫┦஫స⏝ᶵᵓࢆゎ᫂ࡍࡿࡇ࡜ࢆ┠ⓗ࡟ࠊ⁐ᾮ NMR ࢆ⏝࠸࡚ VAP-B MSP ࢻ࣓࢖ࣥཬࡧ VAP-B MSP ࢻ࣓࢖ࣥ࡜Oxysterol Binding Protein (OSBP) ࡢ FFAT motif ࣇࣛࢢ࣓ࣥࢺࡢ」ྜయࡢ❧యᵓ㐀ゎᯒࢆ⾜ࡗࡓࠋNMR࡟ࡼࡿᵓ㐀ゎᯒࠊ⺮ⓑ㉁㛫┦஫స⏝ࠊNMR⁲ᐃᐇ㦂‫ࡿࡓࢃ ࢃࡀ࡜ۑ‬, ࡩࡿ࠸ࡓ ࡁࡻ࠺ࡇ, ࡇࡤࡸࡋ ࡞࠾ࡦࢁ, ࡩࡌࢃࡽ ࡜ࡋࡳࡕ, ࡇࡌࡲࡕࡻ࠺ࡌࢁ࠺

－ 272 －

࠙ᐇ㦂ᡭἲࠚ
኱⭠⳦࡟ࡼࡿⓎ⌧⣔ࢆ⏝࠸࡚13C,15N ᶆ㆑VAP-B MSPࢻ࣓࢖ࣥཬࡧOSBP FFAT motifࣇࣛࢢ࣓ࣥ
ࢺࢆGST⼥ྜ⺮ⓑ㉁࡜ࡋ࡚Ⓨ⌧ࡉࡏࠊࡑࡢᚋ࢔ࣇ࢕ࢽࢸ࢕࣮ࢡ࣐ࣟࢺࢢࣛࣇ࢕࣮ࠊࢤࣝℐ㐣ࢡ࣐ࣟࢺࢢࣛࣇ࢕࣮ࢆ⏝࠸࡚⢭〇ࢆ⾜ࡗࡓࠋᵓ㐀ゎᯒ࡟ᚲせ࡜ࡉࢀࡿ୍㐃ࡢNMR ᐃࢆ⾜࠸ࠊࡑࡢࢹ
࣮ࢱࡢゎᯒసᴗ࡟࠾࠸࡚໬Ꮫࢩࣇࢺࡢᖐᒓ࡟ࡣࢯࣇࢺ࢙࢘࢔SparkyࠊMagRO-NMRViewࠊཬࡧCYANA 㸦FLYAࣔࢪ࣮ࣗࣝ㸧ࢆࠊᵓ㐀ィ⟬࡟ࡣCYANAࢆ⏝࠸ࡓࠋࡲࡓ」ྜయᵓ㐀ゎᯒ࡟㛵ࡋ࡚ࡣࠊ」ྜయᙧᡂ᫬ࡢNMRࢫ࣌ࢡࢺࣝࢆ☜ㄆࡍࡿࡓࡵ࡟1H-15N HSQCࢆ฼⏝ࡋࡓ⁲ᐃᐇ㦂ࢆ⾜ࡗࡓࠋᚓࡽࢀࡓNMRࢫ࣌ࢡࢺࣝࢆཧ⪃࡟」ྜయࡢᵓ㐀ゎᯒࡢࡓࡵࡢNMR ᐃࢆ⾜࠸ࠊࡲࡓࠊ໬Ꮫࢩࣇࢺ
ࡢኚ໬࠿ࡽ┦஫స⏝㡿ᇦࡢ᥎ᐃࢆ⾜ࡗࡓࠋ࠙⤖ᯝ࡜⪃ᐹࠚ
VAP-BࡢMSPࢻ࣓࢖ࣥ࡟㛵ࡋ࡚ࡣ2ࡘࡢĮ࣊ࣜࢵࢡࢫ࡜8ࡘࡢȕࢫࢺࣛࣥࢻ࠿ࡽ࡞ࡿᵓ㐀ࡀᚓࡽࢀࡓ (Figure 1)ࠋ ᪤࡟Ⓨ⾲ࡉࢀ࡚࠸ࡿ⤖ᬗᵓ㐀㸦PDBID 3IKK㸧4࡜ẚ㍑ࡋࡓ࡜ࡇࢁࠊ୧⪅ࡢᵓ㐀ࡣ࠾࠾ࡴࡡ୍⮴ࡋࠊ௒ᅇࡢ⁐ᾮᵓ㐀࡛᪂ࡓ࡟᳨ฟ࡛ࡁࡓ஧ḟᵓ㐀ࡶᏑᅾࡋ࡚࠸ࡓࠋVAP-B-FFAT motif」ྜయᵓ㐀࡟ࡘ࠸࡚ࡢNMR⁲ᐃᐇ㦂࡛ࡣ」ྜయᙧᡂ᫬ࡢNMRࢫ࣌ࢡࢺࣝࢆ☜ㄆࡍࡿࡇ࡜ࡀ࡛ࡁࠊ
ࡲࡓࠊẁ㝵ⓗ࡞OSBPࣇࣛࢢ࣓ࣥࢺࡢῧຍ࡟కࡗ࡚」ᩘࡢṧᇶ࡛໬Ꮫࢩࣇࢺࡢ኱ࡁ࡞ኚ໬ࢆほ ࡋ
ࡓ (Figure 2)ࠋࡇࡢ໬Ꮫࢩࣇࢺࡢኚ໬㔞ࢆ⟬ฟࡋࡓ࡜ࡇࢁࠊࡑࡢ኱ࡁࡉࡢࢺࢵࣉ5ࡣ࠸ࡎࢀࡶVAPA-OSBP (FFAT motif) 」ྜయ࡟࠾ࡅࡿ⤖ྜ㡿ᇦ5࡟┦ᙜࡍࡿ㡿ᇦ࡟఩⨨ࡋ࡚࠸ࡿࡇ࡜ࡀุ᫂ࡋࡓࠋ
ࡲࡓࠊࡇࢀࡽࡢ୰࡟ࡣfALSⓎ⑕࡟㛵୚ࡋ࡚࠸ࡿ࡜ࡉࢀࡿT46ṧᇶࡀྵࡲࢀ࡚࠾ࡾࠊ⚄⤒⑌ᝈ࡟࠾࠸࡚⺮ⓑ㉁㛫ࡢ⤖ྜぶ࿴ᛶࡀపୗࡋ࡚࠸ࡿྍ⬟ᛶࡀ⪃࠼ࡽࢀࡓࠋⓎ⾲࡛ࡣ」ྜయࡢ❧యᵓ㐀ゎᯒࡢ⤖ᯝࢆ♧ࡋࠊ୧⺮ⓑ㉁㛫ࡢ┦஫స⏝ࡢヲ⣽࡟ࡘ࠸࡚ሗ࿌ࡍࡿணᐃ࡛࠶ࡿࠋ

Figure 1 The solution structure of VAP-B MSP

Figure 2 NMR titration experimentdomainMolar ratios (VAP-BMSP : OSBP FFAT) 1:0 (blue),

Superposition of 10 energetically stable structures

1:0.75 (red), 1:2 (green)

obtained

from

CYANA

calculation.

RMSD

0.59±0.12 Ⴒ
References(1) D Peretti et al. Mol. Biol. Cell, 19, 3871-3884 (2008).
(2) AL Nishimura et al., Am J Hum Genet, 75, 822–831 (2004).
(3) S Lua et al., PLoS One, 6, e27072 (2011).
(4) J Shi et al., Biochemistry, 49, 3887-3897 (2010).
(5) K Furuita et al., J Biol Chem, 285, 12961-12970 (2010).

－ 273 －P62Y

DNP-NMR࡟ࡼࡿ࢜ࢡࢱࢹࢩࣝࢩࣜࣝࢩࣜ࢝ࢤࣝ⾲㠃࡟࠾ࡅࡿ࢔
ࣝ࢟ࣝࢫࣝ࣍ࢥࣁࢡ㓟ศᏊ྾╔ᵓ㐀ࡢゎᯒ‫➲ۑ‬ཎஂṊ, 㕥ᮌඞ᫂, ᒸᮧㅍ, 㟷㔝ᜨኴ, 㕥ᮌ୙ᚊ, Ლᘯ඾2
1ⰼ⋤ᰴᘧ఍♫2ி㒔኱Ꮫ໬Ꮫ◊✲ᡤ

DNP-NMR Analysis of Molecular Adsorption of Alkyl Sulfosuccinates on Octadecylsilyl
Silica Surface‫ۑ‬Hisamu Sasahara1, Katsuaki Suzuki2, Satoru Okamura1, Keita Aono1, Furitsu Suzuki1 and Hironori Kaji2
1

Kao Corporation, 1334 Minato, Wakayama 640-8580, Japan

2

Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
Sodium bis(2-ethylhexyl)sulfosuccinate (2EH) is known to have excellent wetting properties among

various surfactants. The adsorption state of 2EH on hydrophobic octadecylsilyl (ODS) silica particle
surface was investigated by DNP-NMR. By mixing 2EH and ODS silica, a downfield shift was observed
for the signals in the high-field (55-80 ppm) region and a change in the signal intensity ratio in the lowfield (160-180 ppm) region. These changes should be attributed to the enhanced signal of the surface of
ODS silica by DNP-NMR. Thus, 2EH could be formed a different association state on the surface of ODS
silica than in the bulk.
⏺㠃άᛶ๣ࡣࡦ࡜ࡘࡢศᏊ୰࡟ぶỈᇶ࡜␯Ỉᇶࢆ᭷ࡍࡿ୧ぶ፹ᛶศᏊ࡛࠶ࡾ㸪≀㉁⏺㠃࡟྾╔ࡍࡿࡇ࡜࡛⏺㠃࢚ࢿࣝࢠ࣮ࢆపୗࡉࡏࡿ㸬⏺㠃࢚ࢿࣝࢠ࣮పୗ࡟ࡼࡗ࡚ࡶࡓࡽࡉࢀࡿங໬࣭ศ
ᩓ࣭⃿ࢀಁ㐍㸦⾲㠃ᨵ㉁స⏝㸧ࡣᵝࠎ࡞⏘ᴗ࡟࠾࠸࡚άⓎ࡟฼⏝ࡉࢀ࡚࠸ࡿ㸬ࡑࡢ୰࡛ࡶ⃿ࢀࡣ⏺㠃άᛶ๣ࡢ㔜せ࡞ᛂ⏝ᡭẁ࡛࠶ࡿ୍᪉࡛㸪ࡑࡢไᚚࡣ」㞧࡛࠶ࡿ1㸬ᅛయ⾲㠃࡟྾╔ࡋࡓᴟᚤ㔞ࡢ⏺㠃άᛶ๣ࡢศᏊ≧ែ࣭㐠ືᛶ࡜⏺㠃࢚ࢿࣝࢠ࣮࡜
ࡢ㛵ಀᛶࡣᮍࡔ༑ศ࡟᫂ࡽ࠿࡟ࡉࢀ࡚࠸࡞࠸㸬ᮏ◊✲࡛

2EH

ࡣDNP-NMRἲࢆ⏝࠸࡚㸪ࣅࢫ(2-࢚ࢳࣝ࣊࢟ࢩࣝ)ࢫࣝ࣍
ࢥࣁࢡ㓟ࢼࢺ࣒ࣜ࢘(2EH)࠾ࡼࡧࡑࡢ␯Ỉ㙐ࡢ␗࡞ࡿ㢮⦕య(Fig. 1)ࡢ࢜ࢡࢱࢹࢩࣝࢩࣜࣝ(ODS)ࢩࣜ࢝ࢤࣝ⢏Ꮚ⾲㠃Hexୖ࡟࠾ࡅࡿ྾╔≧ែࢆ┤᥋ⓗ࡟ほ ࡍࡿࡇ࡜ࢆヨࡳࡓ㸬
2EHࡣඃࢀࡓ⃿ࢀ≉ᛶࢆ᭷ࡍࡿࡀ㸪ࡑࡢ㉳※ࡸไᚚᅉᏊ
ࡣ᫂ࡽ࠿࡟࡞ࡗ࡚࠸࡞࠸㸬␯Ỉ㙐ࡢ␗࡞ࡿࢪ࢔ࣝ࢟ࣝࢫ
ࣝ࣍ࢥࣁࢡ㓟ሷ㢮ࡢỈ⁐ᾮࡣ㸪␯Ỉᛶᅛయ࡟ᑐࡋ࡚␗࡞
ࡿ⃿ࢀ≉ᛶࢆ♧ࡍࡇ࡜࠿ࡽ㸪⃿ࢀ≉ᛶ࡜ᅛయ⾲㠃࡟࠾ࡅࡿྛศᏊࡢ྾╔≧ែࡢ㛵ಀᛶࢆẚ㍑ࡍࡿ㸬

OctFig. 1. Molecular structures of alkyl
sulfosuccinates used in this study.

DNP-NMR ᐃヨᩱ࡜ࡋ࡚㸪㔜Ỉ30 mL࡟⏺㠃άᛶ๣20 mMࢆῧຍࡋ1 h᧠ᢾᚋ㸪ODSࢩࣜ࢝30mgࢆຍ࠼1 h᧠ᢾࡋࡓ㸬ࡑࡢᚋ㸪㐲ᚰศ㞳࡟࡚⏺㠃άᛶ๣Ỉ⁐ᾮࢆศ㞳ࡋ㸪⏺㠃άᛶ๣྾╔ࢩࣜ࢝ࢆస〇ࡋࡓ㸬ࡑࡇ࡟20 mM Amupol in D2O/H2O(9/1)ࢆຍ࠼㸪ᅛయNMR⏝࣮ࣟࢱ࣮࡟඘ሸࡋ㸪ᐃࡋࡓ㸬
DNP-NMR㸪Solid State㸪Surfactant‫ࡴࡉࡦࡽࡣࡉࡉۑ‬㸪ࡍࡎࡁ࠿ࡘ࠶ࡁ㸪࠾࠿ࡴࡽࡉ࡜ࡿ㸪࠶࠾ࡢࡅ࠸ࡓ㸪ࡍࡎࡁࡩࡾࡘ㸪࠿ࡌࡦࢁࡢࡾ

－ 274 －

ᅛయ NMR ࢆ⏝࠸ࡓ DP/MASᐃ࡛ࡣ㸪2EH, ODS ࢩࣜ࢝ࡢ༢⊂ヨᩱ㸦ཎᩱ㸧࡜ 2EH ࢆ྾╔ࡉࡏࡓ ODS ࢩࣜ

2EH+ODS-silica࢝㸦௨ୗ㸪2EH+ODS ࢩࣜ࢝㸧࡟࠾࠸࡚ࢩࢢࢼࣝࡢࢩࣇ

ca. İon/off = 21

ࢺࡸ᪂ࡓ࡞ࢩࢢࢼࣝࣆ࣮ࢡࡣほ ࡉࢀ࡞࠿ࡗࡓ㸬ࡇࢀࡣࣂࣝࢡࡢ 2EH ẚ⋡ࡀ㧗ࡃ㸪ODS ࢩࣜ࢝࡟྾╔ࡋࡓ 2EH࡟⏤᮶ࡍࡿࢩࢢࢼࣝࢆ᳨ฟ࡛ࡁ࡞࠸ࡓࡵ࡛࠶ࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿ㸬ࡑࡇ࡛㸪DNP-NMR ࢆ⏝࠸࡚ឤᗘࢆྥୖࡉ
ࡏࡿࡇ࡜࡟ࡼࡾ㸪ODS ࢩࣜ࢝࡟྾╔ࡋࡓ 2EH ࡢ྾╔≧ែࡢゎ᫂ࢆヨࡳࡓ㸬

Fig. 2. DNP-NMR spectra of ODS-DNP-NMRࢆ⏝࠸ࡓMW=on/off᫬ࡢ2EH+ODSࢩࣜ࢝ࡢ

silica adsorbed with 2EH. Black:

C CP/MASࢫ࣌ࢡࢺࣝࢆFig. 2࡟♧ࡍ㸬ࢧࣥࣉࣝㄪ〇᮲௳

MW=on. Gray: MW=off.

13ࢆ᳨ウࡋࡓ⤖ᯝ㸪MW=on/off࡛⣙21ಸࡢࢩࢢࢼࣝᙉᗘࡢቑ኱ࢆほࡋࡓ㸬≉࡟㸪50 ppmࡼࡾప☢ሙഃࡢࢩࢢࢼࣝࡣ᫂☜࡟ほ ࡛ࡁࡿࡼ࠺࡟࡞ࡿࡇ࡜ࡀࢃ

࠿ࡗࡓ㸬ࡇࡢ⤖ᯝࡣ㸪DNPࢆ⏝࠸᳨࡚ฟឤᗘࢆྥୖࡉࡏࡿࡇ࡜࡛㸪ࢧࣥࣉࣝ⣔୰࡟ᚤ㔞Ꮡᅾࡍࡿ
ODSࢩࣜ࢝࡟྾╔ࡋࡓ2EHࡢᵓ㐀᝟ሗࢆࢫ࣌ࢡࢺࣝ࡜ࡋ࡚ほ ࡛ࡁࡿྍ⬟ᛶࢆ♧၀ࡋ࡚࠸ࡿ㸬ḟ࡟ࠊDNPࢆ⏝࠸ࡎ࡟ ᐃࡋࡓ2EH㸪

abODSࢩࣜ࢝࡜2EH+ODSࢩࣜ࢝ࡢࢫ࣌ࢡ
ࢺࣝ㸪࠾ࡼࡧ㸪DNP࡛ឤᗘࢆྥୖࡉࡏࡓ
2EH㸩ODSࢩࣜ࢝ࡢࢫ࣌ࢡࢺࣝࢆFig. 3࡟♧ࡍ㸬DNP࡟ࡼࡿឤᗘቑ኱࡟ࡼࡗ࡚ᚓ
ࡽࢀࡿ2EH+ODSࢩࣜ࢝ࡢࢫ࣌ࢡࢺ࡛ࣝ

c

2EH

c
c

(A) 2EH+ODS-silica
with DNP
512 scans

d

b d
a

¼5

2EH+ODS-silica(B) without DNP
256 scans

¼5

¼7
¼7

(C) 2EH(D) ODS-silicaࡣ㸪ཎᩱࡸDNPࢆ⏝࠸࡞࠸ሙྜ࡟ࡣほࡉࢀ࡞࠿ࡗࡓࢩࢢࢼࣝࡢࢩࣇࢺࢆほࡋࡓ㸦ᅗ୰c㸪d㸧㸬ࡉࡽ࡟࢝ࣝ࣎ࢽࣝⅣ⣲⏤᮶ࡢࢩࢢࢼࣝ㸦ᅗ୰a㸪b㸧ࡣᙉᗘẚࡀ␗࡞ࡿࡇ࡜ࡀࢃ࠿ࡗࡓ㸬ࡇࢀࡣODSࢩ

13C Chemical shift / ppm

Fig. 3. 13C CP/MAS spectra of (A) 2EH+ODS-silica
with DNP, (B) 2EH+ODS-silica without DNP, (C) 2EH
without DNP and (D) ODS-silica without DNP.

ࣜ࢝࡜ࡢ┦஫స⏝࡟ࡼࡗ࡚㸪2EHࡀࣂࣝࢡ࡜ࡣ␗࡞ࡿᵓ㐀ࢆ࡜ࡿࡇ࡜࡛㸪ࢩࢢࢼࣝࡢࢩࣇࢺࢆ⏕ࡌ࡚࠸ࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿ㸬␯Ỉ㙐ࡢ᰿ඖࡢⅣ⣲࡟⏤᮶ࡍࡿࢩࢢࢼࣝcࡢࢩࣇࢺᖜࡀ኱ࡁ࠸ࡇ࡜
࠿ࡽ㸪ODSࢩࣜ࢝࡟྾╔ࡋࡓ2EHࡣ࢔ࣝ࢟ࣝ㙐ࡢ᰿ඖࡢⅣ⣲ࡀ㛵ಀࡍࡿࣂࣝࢡ࡜ࡣ␗࡞ࡿᵓ㐀ࢆ࡜ࡿࡇ࡜࡛㸪ඃࢀࡓ⃿ࢀ≉ᛶࢆⓎ⌧ࡍࡿ࡜᥎ᐹࡍࡿ㸬DNPࢆ⏝࠸࡞࠸2EH+ODSࢩࣜ࢝ࡢࢫ࣌ࢡࢺ
࡛ࣝࡣࢩࢢࢼࣝࡢࢩࣇࢺࡀほ ࡛ࡁ࡚࠸࡞࠸ࡇ࡜࠿ࡽ㸪ࡇࡢ⤖ᯝࡣDNP-NMRࢆ⏝࠸ࡿࡇ࡜࡛ึࡵ
࡚᫂ࡽ࠿࡜࡞ࡗࡓ࡜⪃࠼ࡿ㸬ᙜ᪥ࡣ㸪 ODSࢩࣜ࢝࡬ࡢ྾╔࡟ࡼࡗ࡚⏕ࡌࡓ2EHࢩࢢࢼࣝࡢࢩࣇࢺࡀ࡝ࡢࡼ࠺࡞ᵓ㐀ኚ໬࡟㉳ᅉࡍࡿ࠿࡟ࡘ࠸࡚㆟ㄽࡍࡿ㸬ࡉࡽ࡟ࠊ⃿ࢀᛶࡀ␗࡞ࡿ2EHࡢ㢮⦕యࢆ⏝࠸ࡓሙྜࡢࢩࢢࢼࣝࡢࢩ
ࣇࢺࡢ᭷↓ࡸ㸪ODSࢩࣜ࢝࡟྾╔ࡋࡓ᫬ࡢ⏺㠃άᛶ๣࡜ODSࢩࣜ࢝ࡢDNP᮲௳ୗ࡛ࡢ⦆࿴᫬㛫ᐃ࡟ࡼࡿศᏊ㐠ືᛶࡢẚ㍑ࢆ⾜࠸㸪2EHࡢඃࢀࡓ⃿ࢀᛶࡢⓎ⌧࡟㔜せ࡞ᅉᏊ࡟ࡘ࠸᳨࡚ウࡋࡓෆᐜ࡟ࡘ࠸࡚ሗ࿌ࡍࡿ㸬
Reference(1) Du, A., Mao, J., Wang, D., Hou, C., Lin, C., Yang, X., Cao, H. and Mao, J. Wettability Alteration at a WaterWet Quartz Surface by a Novel Trimeric Surfactant: Experimental and Theoretical Study. Journal of Molecular
Liquids 354, 118771 (2022).

－ 275 －

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23<B7471/B7=<=4<27D72C/:63;71/:A7<3B/0=:7B37FBC@3A0G&E=7;3<A7=</:FB@/>=:/B32&7;3,3@=
 %#%#  !  # - . 7:=CA63D (, /6</  7/BB=  6:A3<  =<75  %6/>7@=  "/:;3@  @2     G</;71
>@=>3@B73A =4 / BG>3  1/263@7< /263A7D3 2=;/7< 7;>:71/B7=<A 4=@ B63 ;316/<7A; =4 AB@/<2AE/>>7<5 =4
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- ./G/A67%=62/  &63B7;3H3@=%#;3B6=27;>@=D3AB63:7<3/@4@333<3@5G@3:/B7=<A67>
=4/>=:G>3>B72316/7<B6@=C56B63/11C@/B3;3/AC@3;3<B=4@3A72C3A>3174713?C7:70@7C;1=<AB/<BA   

－ 279 －

P65

㔜ඖ⣲ࡢNMR໬Ꮫࢩࣇࢺ⃰ᗘኚ໬࡟㛵ࡍࡿDFTィ⟬: ┦ᑐㄽຠᯝ࡟ᇶ࡙ࡃほ ཎᏊ᰾ෆ࡛ࡢ㟁Ꮚࢫࣆࣥᐦᗘࡢ⌧ࢀ‫ۑ‬ᮅ಴⏤ග㸪᱓ཎ኱௓㸪୰ᕝ┤ဢ
1㟁Ẽ㏻ಙ኱Ꮫ࣭኱Ꮫ㝔᝟ሗ⌮ᕤᏛ◊✲⛉DFT Calculations for Concentration Changes in Heavy-Element Chemical Shifts:
Manifestation of Electron Spin Density in Observed Nuclei Based on Relativistic Effects‫ۑ‬Yoshimitsu Asakura1, Daisuke Kuwahara1, Naoya Nakagawa1
1

Department of Applied Physics, Graduate School of Informatics and Engineering, The University ofElectro-Communications
The NMR chemical shifts for monatomic cations ionized from salt in aqueous solutions often change withthe solution concentration. These changes are referred to herein as dilution–concentration (dc) shifts. We
calculated the dc shifts for various cations in aqueous nitrate solutions of elements in periods 5 and 6 by the
DFT method based on the spin–orbit ZORA Hamiltonian. Furthermore, the electron spin densities of thecations in aqueous nitrate solutions under an external magnetic field were calculated using thematrix/modified Dirac–Kohn–Sham Hamiltonian. We succeeded in clarifying how the dc shifts occur on thehydrated ions of heavy elements.
105໬Ꮫࢩࣇࢺߜࡣᇶ‽≀㉁᰾࡜ほ᰾ࡑࢀࡒࢀࡢ᰾☢Ẽ㐽ⶸᐃᩘߪ ߪୱୟ୫୮୪ୣ ࡢᕪ࡜ࡋ࡚ᐃ⩏ࡉࢀࡿࠋߜ ൌ ߪ െ ߪୱୟ୫୮୪ୣ

(1)㐽ⶸᐃᩘߪࡣ᰾ࢆྲྀࡾᕳࡃ㟁Ꮚࡢ≧ែࠊࡍ࡞ࢃࡕศᏊᵓ㐀ࢆ㗦ᩄ࡟཯ᫎࡍࡿࠋ࠸ࡲࠊሷࢆ⁐ᾮ࡟⁐࠿ࡋࠊ㟁㞳࡟ࡼࡗ࡚༢ཎᏊ࢝ࢳ࢜ࣥ࡜࡞ࡗࡓ᰾ࡢඹ㬆⥺ࢆほ ࡍࡿሙྜࢆ⪃࠼ࡿࠋ⁐ᾮ105࡛ࡣྂࡃ࠿ࡽࠊ⁐ᾮ୰ࡢሷࡢ⃰ᗘ࡟ࡼࡗ࡚ࡑࡢ༢ཎᏊ࢝ࢳ࢜ࣥ᰾ࡢඹ㬆࿘Ἴᩘࡀኚ໬ࡍࡿࡇ࡜ࡀሗ࿌ࡉ
ࢀ࡚ࡁࡓࠋࡇࡢ⌧㇟ࡣḟࡢ஦ᐇ࡟ࡼࡗ࡚ㄝ᫂ࡀ࡞ࡉࢀ࡚࠸ࡿ L 㧗⃰ᗘ࡟࠾࠸࡚ࡣࠊ⁐፹ศᏊ࡜㘒࢖࢜ࣥࢆᙧᡂࡋ࡚࠸ࡿ༢ཎᏊ࢝ࢳ࢜ࣥࡢ࠺ࡕ୍㒊ࡀࠊ㟁㞳ࡋ࡚࠸ࡓ࢔ࢽ࢜ࣥ࡜⤖ྜ࡟ࡼࡗ࡚᪂
ࡓ࡞㘒࢖࢜ࣥࢆᙧᡂࡍࡿࠋ LL ࡑࡢ㘒࢖࢜ࣥᵓ㐀ࡀ105ࡢ᫬㛫ࢫࢣ࣮ࣝ࡟ẚ࡭༑ศ࡞㏿ࡉ࡛ඖ࡟ᡠ
ࡿࡓࡵ࡟ᖹᆒ໬ࡉࢀࡓඹ㬆⥺ࡀほࡉࢀࡿࠋ௚᪉ࠊඹ㬆࿘Ἴᩘࡢ⃰ᗘኚ໬ࡢᐇ㦂್ࢆぢࡿ࡜ࠊ㔜ඖ⣲ࡢ༢ཎᏊ࢝ࢳ࢜ࣥ࡯࡝⃰ᗘኚ໬ࡢ್ࡀ኱ࡁࡃ࡞ࡗ࡚࠸ࡿഴྥࡀぢ࡚ྲྀࢀࡿࠋ⌮ㄽⓗ࡟ࠊߪࡣ┦ᑐㄽⓗ࡞㡯ࢆྵࢇ࡛࠸ࡿࡓࡵࠊୖグࡢഴྥ࡟ࡣ┦ᑐㄽࡀ㛵ಀࡋ࡚࠸ࡿࠋᡃࠎࡣࠊ㔠ᒓ◪㓟ሷࢆỈ࡟⁐࠿ࡋࡓ⣔࡟╔┠ࡋࠊ໬Ꮫࢩࣇࢺ࡟㛵ࡋ࡚㔞Ꮚ໬Ꮫィ⟬ࢆ⾜ࡗࡓࠋࡲࡎほ᰾࡛࠶ࡿ༢ཎᏊ࢝

ࢳ࢜ࣥࡢ࿘ࡾ࡟ỈศᏊࡢࡳࡀ⤖ྜࡋ࡚࠸ࡿỈ࿴࢖࢜ࣥࡢࣔࢹࣝ㸦ᕼ㔘ࣔࢹࣝ㸧࡜ࠊ༢ཎᏊ࢝ࢳ࢜
ࣥ࡟ᑐࡋ◪㓟࢖࢜ࣥࡀ㸯ࡘ⤖ྜࡋࡓỈ࿴࢖࢜ࣥࡢࣔࢹࣝ ⃰⦰ࣔࢹࣝ ࢆ⏝ពࡋࡓࠋࡘࡢࣔࢹࣝࢆ
ᵓ㐀᭱㐺໬ࡋࡓࡢࡕࠊ=HURWKRUGHUUHJXODUDSSUR[LPDWLRQࣁ࣑ࣝࢺࢽ࢔ࣥࢆ⏝࠸ࡓ')7ィ⟬࡟ࡼࡗ࡚ࡑࢀࡒࢀࡢ㐽ⶸᐃᩘࢆィ⟬ࡋࠊࡑࡢᕪ㸦GLOXWLRQFRQFHQWUDWLRQVKLIWGFࢩࣇࢺ㸧ߜ ሺୢୡሻ ࢆồࡵࡓࠋ⤖ᯝࢆ)LJ࡟♧ࡍࠋὀ┠ࡍ࡭ࡁࡇ࡜ࡣࠊ᭱እẆ㟁Ꮚ㓄⨨ࡀVࡢ㔜ඖ⣲࡟࠾࠸࡚GFࢩࣇ
ࢺࡀࠊḟࡢᦤື㸦㌶㐨ࢮ࣮࣐ࣥ┦஫స⏝ࠊࢫࣆࣥ㌶㐨┦஫స⏝ࠊࣇ࢙࣑ࣝ᥋ゐ┦஫స⏝㸧࡟⏤᮶໬Ꮫࢩࣇࢺ㸪┦ᑐㄽⓗ㔞Ꮚ໬Ꮫィ⟬㸪㟁Ꮚࢫࣆࣥᐦᗘ
‫ࡘࡳࡋࡼࡽࡃࡉ࠶ۑ‬㸪ࡃࢃࡣࡽࡔ࠸ࡍࡅ㸪࡞࠿ࡀࢃ࡞࠾ࡸ

－ 280 －

ሺୢୡሻࡍࡿ㐽ⶸᐃᩘߪୗ୓Ȁ୊େ ࡢᕪߜୗ୓Ȁ୊େ ࡟ࡼࡾỴࡲࡗ࡚࠸ࡿࡇ࡜࡛࠶ࡿࠋ᭱
እẆ㟁Ꮚ㓄⨨͸ ଶ ࡢ㔜ඖ⣲࡟ࡔࡅࡇ࠺ࡋࡓ≉ᚩࡀ⌧ࢀࡿ⌮⏤ࡣࠊ௨ୗࡢせ⣲ࡢ」ྜࡢ⤖ᯝ࡟࠶ࡿ࡜
⪃࠼ࡓ㸸ࡲࡎศᏊᵓ㐀ࡢኚ໬࡟㉳ᅉࡍࡿせ⣲࡜ࡋ࡚ࠊձ◪㓟࢖࢜ࣥ࡜ࡢ⤖ྜ࡟ࡼࡾࠊࡘࡢࣔࢹࣝ㛫࡛㔜ඖ⣲ࡢ࣐ࣜࢣࣥ㟁Ⲵࡀ㹼࡯࡝ኚ໬ࡍࡿࡇ࡜ࠋ⥆࠸࡚ߪୗ୓Ȁ୊େ ࡢ࣓࢝ࢽࢬ࣒࡟㛵ࡍࡿせ⣲࡜ࡋ࡚ࠊղእ㒊☢ሙ࡟ࡼࡗ࡚౯
㟁Ꮚ㌶㐨࡟㌶㐨ゅ㐠ື㔞ࢆࡶࡗࡓບ㉳≧ែࡀΰධࡋࠊࢫࣆࣥ㌶㐨
┦஫స⏝࡟ࡼࡿࢫࣆࣥศᴟࡀ㉳ࡇࡿࡇ࡜ࠊճࢫࣆࣥ㌶㐨┦஫స⏝
Fig. 1. Calculated dc shifts for monoatomic cations in aqueous
nitrate solutions of elements in periods 5 and 6, excluding mostof the transition elements.[1]ࡀཎᏊ␒ྕ࡟౫Ꮡࡍࡿࡇ࡜ࠊմ౯
㟁Ꮚ㌶㐨࡟ᙉࡃᏑᅾࡍࡿVᛶ࡟ࡼࡾࣇ࢙࣑ࣝ᥋ゐ┦஫స⏝ࡀ⏕ࡌࡿࡇ࡜ࠊ࡛࠶ࡿࠋ
ᡃࠎࡣࡉࡽ࡟
3E ,, ࡜ &V , ࢆ౛࡜ࡋࠊእ㒊☢ሙࡢࡶ࡜࡛ࡢศᏊࡢ
㟁Ꮚࢫࣆࣥᐦᗘࢆ
')7ィ⟬ࡋࠊྍど໬ࡋࡓ )LJ ࠋࣁ࣑ࣝࢺࢽ࢔ࣥ࡟ࡣ

Fig. 2. Fermi contacts between the nuclei of metal ions and spin-polarized
electrons in aqueous nitrate solutions.[1]

PDWUL[PRGLILHG
'LUDF̽.RKQ̽6KDP
ࣁ࣑ࣝࢺࢽ࢔ࣥࢆ

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ሺୢୡሻࡲࡓߜୗ୓Ȁ୊େ ࡀ࡯࡜ࢇ࡝࡞࠸&V , ࡛ࡣࠊ3E ,, ࡼࡾࡶᑠࡉ࠸,VRPHWULF YDOXH࡛᰾㏆ഐࡢ㟁Ꮚࢫࣆࣥᐦᗘࡀ࡞ࡃ࡞ࡗ࡚࠸ࡿࠊ࡜࠸࠺ࡇ࡜ࡶ☜ㄆ࡛ࡁࡿࠋ௨ୖࠊᮏ◊✲ࡣ㔜ඖ⣲ࢆྵࡴ⁐ᾮ࡟࠾ࡅࡿ
ඹ㬆࿘Ἴᩘࡢᐇ㦂ࢹ࣮ࢱࡀࠊศᏊ㛫ࡢ┦஫స⏝࡜┦ᑐㄽຠᯝ࡟኱ࡁࡃᨭ㓄ࡉࢀ࡚࠸ࡿࡇ࡜ࡢ୍౛
ࢆ♧ࡋࡓࠋᐃࡢ෌⌧ᛶࡢࡓࡵ࡟ࡣࠊ⁐㉁ࡢ⃰ᗘࢆグ㘓ࡍࡿࡇ࡜ࡀ୙ྍḞ࡜ゝ࠼ࡿࡔࢁ࠺ࠋࡲࡓ

KHDY\DWRPHIIHFWRQWKHOLJKWDWRP࡜࠸࠺ほⅬ࠿ࡽࡣࠊ㔜ඖ⣲ࢆྵࡴ⁐ᾮ࡟ᇶ‽≀㉁ࢆᢞධࡍ
ࡿࡇ࡜ࡀᇶ‽≀㉁ࡢࢩࣇࢺ࡟ணᮇࡏࡠኚ໬ࢆࡶࡓࡽࡍࠊ࡜࠸࠺ࡇ࡜࡟ࡶ␃ពࡋ࡞ࡅࢀࡤ࡞ࡽ࡞࠸ࠋ

References(1) Y. Asakura, D. Kuwahara, N. Nakagawa, Journal of Computer Chemistry, Japan -International Edition
2022, 8, 2021.

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P66Y࣑࣮ࣗ࢜ࣆ࢜࢖ࢻཷᐜయࡢ࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮࡟ࡼࡿ
άᛶ໬ᶵᵓࡢゎ᫂‫ۑ‬㔠Ꮚ⯗, 2㸪௒஭㥴㍜1㸪ὸᑿಙኸ1, 2㸪ᖾ⚟⿱2㸪ୖ⏣༟ぢ2㸪ᔱ⏣୍ኵ1
1 ⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮
2 ᮾி኱Ꮫ኱Ꮫ㝔࣭⸆Ꮫ⣔◊✲⛉Activation mechanism of the P-opioid receptor by an allosteric modulator‫ۑ‬Shun Kaneko1, 2, Shunsuke Imai2, Nobuaki Asao1, 2, Yutaka Kofuku2, Takumi Ueda2, Ichio Shimada1
1 RIKEN Center for Biosystems Dynamics Research
2 Graduate School of Pharmaceutical Sciences, The University of Tokyo

The allosteric modulators, which bind to nonorthosteric sites to enhance the signaling activities of Gprotein-coupled receptors (GPCRs), are new candidates for GPCR-targeting drugs. Our solution NMR
analyses of the ȝ-opioid receptor (MOR) revealed that the MOR activity was determined by a conformational
equilibrium between three conformations. Interestingly, an allosteric modulator shifted the equilibrium
toward a conformation with the highest activity to a level that cannot be reached by orthosteric ligands alone,leading to the increased activity of MOR. Our NMR analyses also identified the binding site of the allostericmodulator, including the residues contributing to the regulation of the equilibrium. These findings provide
insights into the rational developments of novel allosteric modulators.
Gࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయ (GPCR) ࡣࠊ⡿ᅜ㣗ရ་⸆ရᒁᢎㄆ⸆ࡢᶆⓗࡢ30㸣௨ୖࢆ༨ࡵࡿࠊ
๰⸆ᶆⓗ࡜ࡋ࡚㔜せ࡞⭷ࢱࣥࣃࢡ㉁ࣇ࢓࣑࣮࡛ࣜ࠶ࡿࠋGPCRᶆⓗ⸆ࡢ࡯࡜ࢇ࡝ࡣ⣽⬊እ࡟࠶ࡿࣜ࢞ࣥࢻ⤖ྜ࣏ࢣࢵࢺ࡟⤖ྜࡋ࡚GPCRࢆάᛶ໬ࡋࠊࡇࡢ᫬࡟࡝ࢀࡔࡅGPCRࡀࢩࢢࢼࣝࢆఏ㐩ࡍࡿ࠿ࡀᐇ㝿ࡢ⸆ຠ࡜┦㛵ࡍࡿࠋ୍᪉ࠊGPCRࡢࣜ࢞ࣥࢻ⤖ྜ࣏ࢣࢵࢺ࡜ࡣ␗࡞ࡿ㒊఩࡟⤖ྜࡋࡑࡢࢩࢢࢼࣝఏ㐩άᛶࢆୖ᪼ࡉࡏࡿ໬ྜ≀ࢆ࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮࡜࿧ࡪࠋ࢔ࣟࢫࢸࣜ
ࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮ࡀ࢔ࢦࢽࢫࢺ࡜ඹ࡟GPCR࡟⤖ྜࡍࡿ࡜ࠊGPCRࡣ࢔ࢦࢽࢫࢺ༢⊂⤖ྜ᫬ࡼࡾࡶᙉࡃάᛶ໬ࡍࡿࡇ࡜࠿ࡽࠊ࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮ࡣࡼࡾ⸆ຠᗘࡢ㧗࠸⸆๣ೃ⿵࡜ࡋ
࡚ᮇᚅࡉࢀ࡚࠸ࡿࠋࡇࢀࡲ࡛࡟ࢡࣛ࢖࢜㟁Ꮚ㢧ᚤ㙾ゎᯒࡸX⥺⤖ᬗᵓ㐀ゎᯒ࡟ࡼࡾ」ᩘࡢGPCR
࡟ࡘ࠸࡚࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮⤖ྜ᫬ࡢᵓ㐀ࡀỴᐃࡉࢀ࡚࠸ࡿࡶࡢࡢࠊࡇࢀࡽࡢᵓ㐀࡛ࡣ࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮ῧຍ࡟క࠺GPCRࡢᵓ㐀ኚ໬ࡣࠊࡑࡢ⤖ྜ㒊఩㏆ഐࢆ㝖࠸࡚࡯࡜ࢇ࡝ほࡉࢀ࡚࠸࡞࠿ࡗࡓࠋࡇࡢࡇ࡜࠿ࡽࠊࡼࡾ⸆ຠᗘࡢ㧗࠸GPCRᶆⓗ⸆ࢆྜ⌮ⓗ࡟タィࡍࡿ࠺࠼࡛ࠊ࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮ࡢ⤖ྜ࡟ࡼࡗ࡚࡞ࡐ࢔ࢦࢽࢫࢺ༢⊂⤖ྜ᫬ࡼࡾࡶ
GPCRࡀᙉࡃάᛶ໬ࡍࡿࡢ࠿ࢆ⌮ゎࡍࡿࡇ࡜ࡀ㔜せ࡞ㄢ㢟࡛࠶ࡗࡓࠋ
㏆ᖺࠊGPCRࡀ」ᩘᵓ㐀ࢆ஺᥮ࡍࡿືⓗ࡞ᛶ㉁ࢆᣢࡕࡑࡢືⓗᛶ㉁ࡀάᛶ࡟㔜せ࡛࠶ࡿࡇ࡜ࠊ
ࡇ࠺ࡋࡓືⓗᛶ㉁ࡢゎᯒ࡟⁐ᾮNMRἲࡀຠᯝⓗ࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀ࡚࠸ࡿ[1]ࠋࡑࡇ࡛ᮏ◊✲࡛ࡣࠊ࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮࡟ࡼࡿGPCRࡢάᛶ໬ᶵᵓࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵࠊ௦⾲ⓗ࡞
GPCRࡢ1✀࡛࠶ࡿP࢜ࣆ࢜࢖ࢻཷᐜయ (MOR) ࢆᑐ㇟࡟⁐ᾮNMRἲ࡟ࡼࡿゎᯒࢆ⾜ࡗࡓ[2]ࠋ࣓ࢳ
࢜ࢽ࣓ࣥࢳࣝᇶࢆ13Cᶆ㆑ࡋࡓMORࢆㄪ〇ࡋࠊᵝࠎ࡞ࣜ࢞ࣥࢻᏑᅾୗ࡛ࡢ࢔ࣟࢫࢸࣜࢵࢡࣔࢪࣗ
࣮ࣞࢱ࣮BMS-986122ῧຍ๓ᚋ࡛ࡢ1H-13C HMQCࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓ⤖ᯝࠊM283⏤᮶ࡢNMRࢩ
Gࢱࣥࣃࢡ㉁ඹᙺᆺཷᐜయ㸪solvent PRE㸪ᵓ㐀ᖹ⾮‫ࢇࡹࡋࡇࡡ࠿ۑ‬㸪࠸ࡲ࠸ࡋࡹࢇࡍࡅ㸪࠶ࡉ࠾ࡢࡪ࠶ࡁ㸪ࡇ࠺ࡩࡃࡺࡓ࠿㸪࠺࠼ࡔࡓࡃࡳ㸪ࡋࡲࡔ࠸ࡕ࠾

－ 282 －

ࢢࢼࣝࡀ᭱኱࡛3ಶほ ࡉࢀྛࢩࢢࢼࣝࡢᏑᅾẚࡀ᮲௳࡟ࡼࡾኚ໬ࡋࡓࡇ࡜࠿ࡽࠊMORࡢM283㏆
ഐࡀ3≧ែࢆ஺᥮ࡍࡿᵓ㐀ᖹ⾮୰࡟࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓ(Fig. A)ࠋྛ᮲௳࡛ࡢMORࡢάᛶ࡜M283⏤᮶ࡢ3ࡘࡢࢩࢢࢼࣝࡢᏑᅾẚࡢẚ㍑࠿ࡽࠊᵓ㐀ᖹ⾮୰ࡢ3≧ែࡀࡑࢀࡒࢀάᛶࡢ␗࡞ࡿ≧ែࢆ཯ᫎࡋ࡚࠾ࡾࡑࡢᏑᅾẚࡀMORࡢぢ࠿ࡅࡢάᛶࢆつᐃࡍࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋBMS-986122ῧຍ᫬࡟ࡣᵓ㐀ᖹ⾮୰ࡢ᭱ࡶάᛶࡢ㧗࠸ᵓ㐀ࡢᏑᅾẚࡀቑຍࡋ࡚࠸ࡓࡇ࡜࠿ࡽࠊBMS-986122ࡀMORࡢᵓ㐀ᖹ⾮ࢆࢩࣇࢺࡉࡏࡿࡇ࡜࡛ࢩࢢࢼࣝఏ㐩άᛶࢆୖ᪼ࡉࡏࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋ
ࡲࡓࠊMORࡢ࣓ࢳ࢜ࢽࣥࡢ࠺ࡕࠊM153, M163, M245ࡢNMRࢩࢢࢼࣝ࡟BMS-986122ῧຍ࡟క࠺
㢧ⴭ࡞໬Ꮫࢩࣇࢺኚ໬ࡶࡋࡃࡣᗈᖜ໬ࡀほࡉࢀࡓࡇ࡜࠿ࡽࠊࡇࢀࡽࡢṧᇶ㏆ഐ࡟BMS-986122

ࡀ⤖ྜࡍࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋࡇࢀࡽࡢṧᇶ㏆ഐࡢศᏊ⾲㠃ࡣ࣏ࢣࢵࢺ≧ࡢᵓ㐀ࢆᙧᡂࡋ࡚࠾ࡾࠊ
ࡇࡢ࣏ࢣࢵࢺࢆᙧᡂࡍࡿṧᇶ࡟ኚ␗ࢆᑟධࡋࡓT162Mኚ␗య࡛ࡣBMS-986122࡟ࡼࡿάᛶୖ᪼ࡀほࡉࢀ࡞ࡃ࡞ࡗࡓࡇ࡜࠿ࡽࠊBMS-986122ࡀT162㏆ഐࡢ࣏ࢣࢵࢺ࡟⤖ྜࡍࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋ௨ୖࡢ⤖ᯝࡼࡾࠊ௨ୗࡢࣔࢹࣝࢆᥦၐࡍࡿࠋT162ࡀ࠶ࡿTM3ࡣࠊάᛶ࡜㛵㐃ࡍࡿᵓ㐀ᖹ⾮ࡀほࡉࢀࡓM283ࡀᏑᅾࡍࡿTM6࡜⭷㈏㏻㡿ᇦ࡟࡚㞄᥋ࡋ࡚࠾ࡾࠊBMS-986122ࡀTM3࡜TM6ࡢ㛫ࡢ┦஫స⏝࡟ᦤືࢆ୚࠼ࡿࡇ࡜࡛TM6ࡢᵓ㐀ᖹ⾮ࢆไᚚࡋ࡚࠸ࡿࠋ⣽⬊እഃ࣏ࢣࢵࢺ࡟⤖ྜࡍࡿࣜ࢞ࣥࢻ࡛ࡣࠊࡇࡢ⭷㈏㏻㡿ᇦࡢ┦஫స⏝㡿ᇦࡲ࡛ຠ⋡ⓗ࡟ᵓ㐀ኚ໬ࢆఏ᧛࡛ࡁ࡞࠸ࡓࡵTM6ࡢᵓ㐀ᖹ⾮ࢆ᏶඲࡟ࡣ೫ࡽࡏࡿࡇ࡜ࡀฟ᮶࡞࠸୍᪉࡛ࠊ࢔ࣟࢫࢸࣜࢵࢡࣔࢪ࣮ࣗࣞࢱ࣮ࡣ⭷㈏㏻㡿ᇦࡢ┦஫స⏝ࢆ┤᥋ኚㄪࡍࡿࡇ࡜࡛ᚑ᮶ࡢࣜ࢞ࣥࢻࡼࡾࡶάᛶࡢ㧗࠸ᵓ㐀ࡢᏑᅾẚࢆቑຍࡉࡏࠊ
MORࡢࢩࢢࢼࣝఏ㐩άᛶࢆୖ᪼ࡉࡏࡿࡇ࡜ࡀฟ᮶ࡿ (Fig. B, C)ࠋࡇࢀࡽࡢ⤖ᯝࡣࠊGPCR㛵㐃⑌
ᝈ࡟ᑐࡍࡿ᭷ຠ࡞᪂つ἞⒪⸆ࡢ㛤Ⓨ᪉㔪ࢆᥦ♧ࡍࡿࡶࡢ࡛࠶ࡿࠋ
[1] Shimada I, Ueda T, Kofuku Y, Eddy MT, and Wüthrich K. (2019) GPCR drug discovery: integrating
solution NMR data with crystal and cryo-EM structures. Nat. Rev. Drug Discov. 18(1):59-82.
[2] Kaneko S, Imai S, Asao N, Kofuku Y, Ueda T, and Shimada I. (2022) Activation mechanism of the ȝopioid receptor by an allosteric modulator. Proc. Natl. Acad. Sci. U.S.A. 119(16):e2121918119.

Fig. A. 1H-13C HMQC signals from M283 of MOR or N152A variant in the antagonist naloxone-bound,the partial agonist morphine-bound, and the full agonist DAMGO-bound states, in the absence andpresence of the allosteric modulator BMS-986122. N152A variant has higher activity than parental MOR.
Fig. B, C. Models of function-related conformational equilibrium of MOR in the full agonist DAMGObound state (B) and the DAMGO-bound state in the presence of BMS-986122 (C).

－ 283 －

P67࣐ࣝࢳࢻ࣓࢖ࣥ⺮ⓑ㉁GRB2࡜SOS1-PRM㡿ᇦࡢ┦஫స⏝ゎᯒ‫ۑ‬㤋㔝᱇ኴ1㸪Ⳣ⃝ࡣࡿ࠿㸯㸪Ᏻ⸨Ꮥྐ㸯㸪⏣➃┿ᙬᏊ㸯㸪⨾ᕝ ົ㸰㸪⊦⫤᫭௓㸯㸪⏥ᩫⲮṇᜏ㸯㸪୕ᓥṇつ1,*㸪ᮡ⏣᭷἞3㸪ụ㇂㕲ර㸯㸪ఀ⸨ 㝯㸯1ᮾி㒔❧኱Ꮫ࣭኱Ꮫ㝔⌮Ꮫ◊✲⛉㸪2⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮㸪3⌮໬Ꮫ◊✲ᡤ࣭ᮡ⏣⌮ㄽศᏊ⛉Ꮫ◊✲ᐊ*ᮾி⸆⛉኱Ꮫ࣭⸆Ꮫ㒊

Solution NMR analysis reveals different binding modes on the interaction between ahuman multi-domain protein GRB2 and human SOS1-PRMs‫ۑ‬Keita Tateno1, Haruka Sugasawa1, Takami Ando1, Maako Tabata1, Tsutomu Mikawa2, Kohsuke Inomata1,
Masatsune Kainosho1, Masaki Mishima1,*, Yuji Sugita3, Teppei Ikeya1, and Yutaka Ito1
1

Department of Chemistry, Tokyo Metropolitan University; 2RIKEN Center for Biosystems Dynamics

Research; 3Theoretical Molecular Science Laboratory, RIKEN; *Present address: School of Pharmacy,
Tokyo University of Pharmacy and Life Sciences

Human GRB2 is one of the key mediators in the MAPK signal pathway and transmits a signal froma receptor Tyr kinase on the transmembrane to SOS1, a RAS guanine nucleotide exchange factor (GEF).
Recent studies show that GRB2 is also a major component for liquid-liquid phase separation (LLPS) in
the MAPK signalling by acting as a scaffold for other proteins. While the interactions among two SH3
domains of GRB2 and ten putative proline-rich motifs (PRMs) in the disordered region of SOS1 are thought
to be crucial for the LLPS formation, its molecular recognition mechanism has not yet been revealed
experimentally. We therefore investigated the structural basis of the GRB2-SOS1 interaction by NMR
titration experiments of GRB2 with SOS1-derived proline-rich peptides as well as the whole disorderedregion of SOS1 containing all PRMs. Docking simulation based on the experimental data was also performed.
Our results suggest that the two SH3 domains of GRB2 and ten putative PPMs of SOS1 interact with different
binding affinities and yield complex networks in condensed droplets.
䛆ᗎㄽ䛇䛇㻌 䝠䝖GRB2䛿䠈3䛴䛾䝗䝯䜲䞁䠄NSH3-SH2-CSH3䠅䛷 ᵓ ᡂ 䛥 䜜 䜛 䝬 䝹 䝏 䝗 䝯 䜲 䞁 ⺮ ⓑ ㉁ 䛷 䛒 䜛 䠊 GRB2 䛿
MAPK⤒㊰䛻ᒓ䛧䛶䛚䜚䠈⣽⬊⭷ୖ䛾ཷᐜయ⺮ⓑ㉁䛛䜙
䛾่⃭䜢RAS䛾䜾䜰䝙䞁䝚䜽䝺䜸䝏䝗஺᥮ᅉᏊ䠄GEF䠅䛷䛒䜛SOS1䛻ఏ䛘䜛ᙺ๭䜢ᣢ䛴䠊GRB2䛾2䛴䛾SH3䝗䝯䜲
䞁䛿䠈SOS1䛾Cᮎ➃ኳ↛ኚᛶ㡿ᇦ䛻䛒䜛proline richmotifs䠄PRMs䠅䛸⤖ྜ䛩䜛䛣䛸䛜▱䜙䜜䛶䛔䜛䠊SOS1䛾
PRM 䛸 䛧䛶 䛿 10 䛛ᡤ 䠄 S1-S10 䠅 䛜 ᥎ ᐃ 䛥 䜜 䛶 䛚 䜚 [1] 䠈
GRB2-SOS1」ྜయᙧᡂ䛷䛿䠈」ᩘ䛾␗䛺䜛⤖ྜ䜢௓䛧䛯ከ㠃ⓗ䛺┦஫స⏝䝰䝕䝹䛜ᥦ᱌䛥䜜䛶䛔䜛䠄F
Fig.. 1䠅䠊㏆
ᖺ䠈GRB2䛸SOS1䛿䠈⭷ཷᐜయ䛷䛒䜛LAT䠄linker for
activation of T cells䠅䛸3ศᏊ䛷ᾮᾮ┦ศ㞳䠄LLPS䠅䜢ᙧᡂ䛩䜛䛣䛸䛜ሗ࿌䛥䜜䠈䛣䜜䛜⣽⬊ෆ䝅䜾䝘䝹ఏ㐩䛾ᙉᙅ

Fig. 1 A schematic illustration of theputative model on the molecular interactionin the LLPS formation via GRB2 and SOS1
proline rich motifs (PRMs). The S1-S10
represent PPMs. The boxes surrounded bybold lines indicate PPMs used as SOS1derived peptides in this study.

___________________________________________________________________________________┦஫స⏝ゎᯒ䠈䝬䝹䝏䝗䝯䜲䞁⺮ⓑ㉁䠈LLPS
䕿䛯䛶䛾䛡䛔䛯䠈䛩䛜䛥䜟䛿䜛䛛䠈䛒䜣䛹䛖䛯䛛䜏䠈䛯䜀䛯䜎䛒䛣䠈䜏䛛䜟䛴䛸䜐䠈䛔䛾䜎䛯䛣䛖䛩䛡䠈䛛䛔䛾䛧䜗䛖䜎䛥䛴䛽䠈䜏䛧䜎䜎䛥䛝䠈䛩䛞䛯䜖䛖䛨䠈䛔䛡䜔䛶䛳䜊䛔䠈䛔䛸䛖䜖䛯䛛－ 284 －

䜢ㄪ⠇䛧䛶䛔䜛ྍ⬟ᛶ䛜♧၀䛥䜜䛶䛔䜛[2]䠊䛣䛖䛧䛯
MAPK䝅䜾䝘䝹䛾ఏ㐩䛸LLPS䛾ᙧᡂ䛻䛿䠈GRB2SOS1㛫䛾」ᩘ䛾ᯫᶫᵓ㐀䛜ᚲ㡲䛷䛒䜛䛸⪃䛘䜙䜜䜛䛜䠈䛣䜜䜎䛷䛾ሗ࿌䛷䛿䠈GRB2䛾ྛSH3䝗䝯䜲䞁༢య䛸 SOS1⏤᮶䛾PRM䝨 䝥䝏䝗 䜢⏝䛔䛯ゎᯒ 䛧䛛 䛺䛟[1]䠈඲㛗GRB2䛚䜘䜃SOS1䛾PRMs䜢ྵ䜐㡿ᇦ඲య䜢⏝䛔䛯ヲ⣽䛺┦஫స⏝ゎᯒ䛜ᮇᚅ䛥䜜䛶䛔䛯䠊䛭䛣䛷ᮏ◊✲䛷䛿䠈඲㛗GRB2䛸SOS1䛾PRM䝨䝥䝏䝗䠈䛚䜘䜃SOS1 Cᮎ➃㡿ᇦ䛸䛾NMR⁲ᐃᐇ㦂䜢⾜䛖䛣䛸䛷䠈GRB2䛾2䛴䛾SH3䝗䝯䜲䞁䛸䠈」ᩘ䛾SOS1
PRM䛸䛾༠ዌⓗ┦஫స⏝䛾ゎ᫂䜢ヨ䜏䛯䠊䛆 ᐇ 㦂 䛇 㻌 15N ᶆ ㆑ GRB2 䛻 ᑐ 䛩 䜛 㠀 ᶆ ㆑ SOS1 䛸 䛾
NMR⁲ᐃᐇ㦂䜢⾜䛳䛯䠊SOS1ヨᩱ䛸䛧䛶䛿䠈10䛛ᡤ䛾PRM䛾䛖䛱䠈⤖ྜぶ࿴ᛶ䛾㧗䛔䛸ண᝿䛥䜜䛶䛔䜛4✀㢮䛾䝨䝥䝏䝗䛸䠈10䛛ᡤ䛩䜉䛶䛾PRM䜢ྵ䜐SOS1 Cᮎ➃㡿ᇦ඲య䜢⏝䛔䛯䠊ලయⓗ䛻䛿䠈᪤ሗ䜢ཧ⪃䛻[1]䠈NSH3䝗䝯䜲䞁䛻ᑐ䛧䛶1-3␒┠䛻㧗䛔ぶ࿴ᛶ䜢ᣢ䛴S4, S5, S9䝨䝥䝏䝗䛸䠈၏୍NSH3䝗䝯䜲䞁䜘䜚CSH3
䝗䝯䜲䞁䛸䛾⤖ྜ⬟䛜㧗䛔䛸䛥䜜䜛S10䝨䝥䝏䝗䜢㑅ᢥ䛧䛯䠊䜎䛯䠈GRB2䛻䛴䛔䛶䛿䠈Ᏻᐃᛶྥୖ䜢ᅗ䜛䛯䜑䠈ඛ⾜◊✲䜢ཧ⪃䛻2䛴䛾Cysṧᇶ䜢⨨᥮䛧䛯GRB2
䠄C32S/C198A䠅䜢⏝䛔䛯[3]䠊

Fig. 2 NMR titration experiment of 15N-GRB2
with SOS1 peptides. (a) Overlays of 2D 1H-15N
HSQC spectra from multipoint titrations of 15NGRB2 with S4 peptide. The colour codes
showing the molar ratio of GRB2:S4 peptide areas follows: light grey (1:0), grey (1:0.5), andblack (1:2). Representative cross peaks
exhibiting large chemical shift perturbations areannotated in boxes. (b) KD values for the SOS1
peptides calculated by using the TITAN
software.

䛆 ⤖ᯝ䛸⪃ᐹ䛇䛇 㻌 SOS1⏤᮶䛾䝨䝥䝏䝗⁲ᐃᐇ㦂䛾⤖ᯝ䠈2䛴䛾SH3䝗䝯䜲䞁⏤᮶䛾䝢䞊䜽䛻኱䛝䛺໬Ꮫ䝅䝣䝖
Fig.. 2a䠅.䜎䛯䠈TITAN䝋䝣䝖䜴䜵䜰ኚ໬䛜ほ 䛥䜜䛯䠄F
䜢⏝䛔䛶2D⥺ᙧゎᯒ䜢⾜䛔䠈ྛSH3䝗䝯䜲䞁䛻ᑐ䛩䜛
SOS1䝨䝥䝏䝗䛾ゎ㞳ᐃᩘ䠄KD䠅䜢ィ⟬䛧䛯䠄F
Fig.. 2b䠅.
ゎᯒ䛾⤖ᯝ䠈S4, S5, S9䛿NSH3䝗䝯䜲䞁䛻䠈S10䛿CSH3䝗䝯䜲䞁䛻䜘䜚ᙉ䛟⤖ྜ䛩䜛䛣䛸䛜䜟䛛䛳䛯䠊ᚓ
䜙䜜䛯KD䛾ഴྥ䛿䠈GRB2䛾SH3䝗䝯䜲䞁༢య䜢฼⏝䛧䛯᪤ሗ[1]䛾⤖ᯝ䛸ྠᵝ䛷䛒䜛䛣䛸䛜ศ䛛䛳䛯䠊
SOS1 Cᮎ➃㡿ᇦ䜢⏝䛔䛯⁲ᐃᐇ㦂䛷䛿䠈୺䛻GRB2 SH3䝗䝯䜲䞁䛻䛚䛔䛶䝢䞊䜽䛾ῶ⾶䛜ほ 䛥䜜
Fig.. 3aa & 3b䠅䠊䜎䛯䠈䝢䞊䜽䛾ῶ⾶䛿CSH3䝗䝯䜲䞁䛾ṧᇶ䜘䜚䜒NSH3䝗䝯䜲䞁䛾ṧᇶ䛜ඃඛⓗ䛻㉳䛯䠄F䛣䜛䛣䛸䛛䜙䠈SOS1䛿CSH3䝗䝯䜲䞁䜘䜚䜒NSH3䝗䝯䜲䞁䛸ᙉ䛟⤖ྜ䛧䛶䛔䜛䛣䛸䛜♧၀䛥䜜䛯䠊䛣䜜䛿䠈
SOS1 ෆ 䛻 NSH3 䝗 䝯 䜲 䞁 ≉ ᭷ 䛾 ⤖ ྜ 䝰 䝏 䞊 䝣䠄PxxPxR䠅䛜䛒䜛୍᪉䛷䠈CSH3䝗䝯䜲䞁≉᭷䛾⤖ྜ䝰䝏䞊䝣䠄PxxxRxxKP䠅䛜Ꮡᅾ䛧䛺䛔䛸䛔䛖᪤ሗ䛾⤖ᯝ䜢ᨭᣢ䛩䜛䜒䛾䛷䛒䜛䠊⌧ᅾ䛿䠈⁐ᾮ୰䛷䛾GRB2䛸SOS1 Cᮎ➃㡿ᇦ䛾䜘䜚ヲ⣽䛺ศᏊㄆ㆑ᶵᵓ䜢᫂䜙䛛䛻䛩䜛䛯䜑䛻䠈䝯䝏䝹ᇶ㑅ᢥⓗᶆ㆑ヨᩱ䜢฼⏝䛧䛯⁲ᐃᐇ㦂䜔䠈ᐇ㦂䝕䞊䝍䜢䝗䝑䜻䞁䜾䝅䝭䝳䝺䞊䝅䝵䞁䛸⤌䜏ྜ䜟䛫䛯ゎᯒ䛻ྲྀ䜚⤌䜣䛷䛔䜛䠊
࠙ཧ⪃ᩥ⊩ࠚ[1] Liao, T.-J. et al., J. Am. Chem. Soc 142,
3401-3411 (2020); [2] Su, X. et al., Science 352, 595-599(2016); [3] Yuzawa, S. et al., J. Mol. Biol, 306, 527-537(2001).

－ 285 －

Fig. 3 Intensity ratios from NMR titration
experiments of 15N-GRB2 with SOS1 Cterminal disordered region. Unassigned residues
are shown in grey. GRB2:SOS1 = 1:0.125 (a)and GRB2:SOS1 = 1:1 (b)P68Yᖖ☢ᛶNMRࢆ⏝࠸ࡓ࣐ࣝࢳࢻ࣓࢖ࣥ⺮ⓑ㉁GRB2ࡢ❧యᵓ㐀ゎᯒżᏳ⸨⪃ྐ1㸪Ⳣ⃝ࡣࡿ࠿1㸪㤋㔝ᆂኴ1㸪⏣➃┿ᙬᏊ1㸪⨾ᕝ ົ2㸪ᐑ㔝ධὒᖹ3㸪
ᕝ➃ᗤᖹ4㸪Hisham Dokainish5㸪Weitong Ren5㸪኱ฟ┿ኸ5㸪ᑎෆ ຮ6㸪
⊦⫤᫭௓1㸪୕ᓥṇつ7㸪⏥ᩫⲮṇᜏ1㸪ᮡ⏣᭷἞5㸪ụ㇂㕲ර1㸪ఀ⸨ 㝯11ᮾி㒔❧኱Ꮫ࣭኱Ꮫ㝔⌮Ꮫ◊✲⛉㸪2⌮໬Ꮫ◊✲⛉ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮㸪3኱㜰኱Ꮫ࣭⺮ⓑ㉁◊✲ᡤ㸪4㓗㎰Ꮫᅬ኱Ꮫ࣭㣗࡜೺ᗣᏛ㢮㸪5⌮໬Ꮫ◊✲ᡤ࣭ᮡ⏣⌮ㄽศᏊ໬Ꮫ◊✲ᐊ㸪6ኴ㝧᪥㓟࣭SI࢖ࣀ࣮࣋ࢩࣙࣥࢭࣥࢱ࣮㸪7ᮾி⸆⛉኱Ꮫ࣭⸆Ꮫ㒊

Structure determination of a human multi-domain protein, GRB2, by paramagnetic
NMRżTakami Ando1, Haruka Sugasawa1, Keita Tateno1,Maako Tabata1, Tsutomu Mikawa2, Miyanoiri Youhei3,
Youhei Kawabata4, Hisham Dokainish5, Weitong Ren5, Mao Oide5, Tsutomu Terauchi6㸪
Kohsuke Inomata1, Masaki Mishima7, Masatsune Kainosho1, Yuji Sugita5, Teppei Ikeya1, Yutaka Ito1
1
Department of Chemistry, Graduate School of Science, Tokyo Metropolitan University
2
RIKEN Center for Biosystem Dynamics Research
3
Institute for Protein Research, Osaka University
4
Department of Food Science and Human Wellness, Rakuno Gakuen University
5
Theoretical Molecular Science Laboratory, RIKEN Cluster for Pioneering Research
6
SI Innovation Center, Taiyo Nippon Sanso Corporation
7
School of Pharmacy, Tokyo University of Pharmacy and Life Sciences

Human GRB2 is one of the key mediators in the upstream process of the Ras-mediated signal transduction
pathway. It consists of three functional domains, nSH3-SH2-cSH3, connecting with flexible linkers. Whilethe 3D structure of GRB2 has been determined by X-ray crystallography, the studies of SAXS and MD
simulation have proposed that the relative orientation of the domains and the inter-domain interactions inaqueous solution would be different from that in the crystal. The domain orientation is thought to be
responsible for its biological functions and the formation of liquid-liquid phase separation (LLPS) via GRB2.
Thus, we performed the protein structure determination of GRB2 using NOEs, paramagnetic relaxation
enhancements (PREs), and residual dipolar coupling (RDCs) for inter-domain structural constraints. In
addition to the conventional NMR structure calculation, we also addressed the multi-state structure
determination since it was considered that various conformations exist in solution due to its flexible linkers. ࠙ᗎㄽࠚࣄࢺGRB2 (217ṧᇶ) ࡣཎ ࡀ ࢇ 㑇 ఏ Ꮚ ⏘ ≀ RASࡀ 㛵 ୚ ࡍ ࡿ ࢩ ࢢ ࢼ ࣝ ఏ 㐩 ⤒ ㊰ ࡛ ാ ࡃ࢔ࢲࣉࢱ࣮⺮ⓑ㉁࡛࠶ࡿ㸬3ࡘࡢᶵ⬟ࢻ࣓࢖ࣥ (nSH3-SH2-cSH3) ࡀᰂ㌾࡞࣮࡛ࣜࣥ࢝⧅ࡀࢀࡓ࣐
ࣝࢳࢻ࣓࢖ࣥ⺮ⓑ㉁࡛࠶ࡾ㸪SH2ࢆ௓ࡋ࡚ཷᐜయᆺࢳࣟࢩࣥ࢟ࢼ࣮ࢮ࡜㸪ࡲࡓSH3ࢻ࣓࢖ࣥࢆ௓ࡋ
࡚proline rich motifࢆᣢࡘ⺮ⓑ㉁࡜⤖ྜࡍࡿࡇ࡜࡛᝟ሗࢆఏ࠼ࡿ㸬඲ 㛗 GRB2ࡢ X⥺ ⤖ ᬗ ᵓ 㐀 ࡣ᪤ ࡟ ሗ ࿌ ࡉ ࢀ ࡚ ࠸ ࡿ ࡀ [1]㸪 X⥺ ᑠ ゅ ᩓ ஘ (SAXS) ࡸ ศ Ꮚ ື ຊ Ꮫ (MD) ࢩ ࣑ ࣗ ࣞ ࣮ ࢩ ࣙࣥ ࡢ ⤖ ᯝ ࠿ ࡽ ࡣ 㸪⁐ ᾮ ≧ ែ ࡛ ࡣ ⤖ ᬗ ᵓ 㐀 ࡜ ␗ ࡞ ࡗ ࡓ ࢻ ࣓ ࢖ ࣥ 㛫 ┦ ᑐ 㓄 ⨨ ࢆ ྲྀ ࡿ ྍ ⬟ ᛶ ࡀ❧యᵓ㐀㸪ᖖ☢ᛶNMR㸪࣐ࣝࢳࢻ࣓࢖ࣥ⺮ⓑ㉁ż࠶ࢇ࡝࠺ࡓ࠿ࡳ㸪ࡍࡀࡉࢃࡣࡿ࠿㸪ࡓ࡚ࡢࡅ࠸ࡓ㸪ࡓࡤࡓࡲ࠶ࡇ㸪ࡳ࠿ࢃࡘ࡜ࡴ㸪ࡳࡸࡢ࠸ࡾࡼ࠺࡬࠸㸪࠿ࢃࡤࡓࡼ࠺࡬࠸㸪ࡦࡋࡷࡴ࡝࠿࠸࡟ࡗࡋࡹ㸪ࢀࢇ࠺࠻࠸࡜ࢇ㸪࠾࠾࠸࡛ࡲ࠾㸪࡚ࡽ࠺ࡕࡘ࡜ࡴ㸪࠸ࡢࡲࡓࡇ࠺ࡍࡅ㸪ࡳࡋࡲࡲࡉࡁ㸪࠿࠸ࡢࡋࡻ࠺ࡲࡉࡘࡡ㸪ࡍࡂࡓࡺ࠺ࡌ㸪࠸ࡅࡸ࡚ࡗ࡮࠸㸪࠸࡜࠺ࡺࡓ࠿

－ 286 －♧ ၀ ࡉ ࢀ ࡓ [2]㸬ࡲ ࡓ ᭱ ㏆ 㸪GRB2ࢆ ௓ ࡋ ࡓ ᾮ ᾮ ┦ ศ 㞳 (LLPS)ࡀ 」 ᩘ ሗ ࿌ ࡉ ࢀ ࡚ ࠾ ࡾ 㸪ࡇࡢ ┦ ศ 㞳 ࡀ ࢩ ࢢ ࢼ ࣝ ఏ 㐩 ⤒ ㊰ ࡢ ಙ ྕ ᙉ ᗘ ࢆ ㄪ ᩚ ࡋ ࡚ ࠸ ࡿ ࡜ ࠸ ࠺ ㆟ ㄽ ࡶ ࠶ ࡿ [3]㸬ࡇ ࠺ ࡋ ࡓ
GRB2ࢆ ௓ ࡋ ࡓ ┦ ศ 㞳 ࡢ ᙧ ᡂ ࡜ ஋ 㞳 ࡣ 㸪 GRB2ࡢ 3ࡘ ࡢ ࢻ ࣓ ࢖ ࣥ ࡢ ⁐ ᾮ ୰ ࡛ ࡢ ┦ ᑐ 㓄 ⨨ ࡀ㛵 ୚ ࡋ ࡚ ࠸ ࡿ ࡜ ண ᝿ ࡉ ࢀ ࡓ 㸬ࡑ ࡇ ࡛ ᮏ ◊ ✲ ࡛ ࡣ 㸪⏕ ⌮ ⓗ ᮲ ௳ ࡛ ࡢ ᵓ 㐀࣭ᶵ ⬟ ┦ 㛵 ࡢ ゎ ᫂ࢆ ┠ ᣦ ࡋ ࡚ 㸪ᖖ ☢ ᛶ NMRࢆ ⏝ ࠸ ࡓ GRB2ࡢ ❧ య ᵓ 㐀 ゎ ᯒ ࢆ ヨ ࡳ ࡓ 㸬GRB2ࡢ ࢻ ࣓ ࢖ ࣥ ┦ ᑐ㓄 ⨨ ࡣ 㸪 」 ᩘ ࢥࣥࣇ࢛࣓࣮ࢩࣙࣥࡀᏑᅾࡍࡿ࡜ண᝿ࡉࢀࡓࡓࡵ㸪」ᩘ≧ែࢆ௬ᐃࡋࡓmulti-state❧యᵓ㐀ィ⟬ࢆᐇ⾜ࡋ㸪GRB2ࡢ⁐ᾮ୰࡛ࡢ࢔ࣥࢧࣥࣈࣝᵓ㐀ࡢྍど໬ࢆ┠ᣦࡋࡓ㸬ࡲࡓ㸪SAXS
ࡸືⓗගᩓ஘ (DLS) ࡢᐃࡸ㸪MDࢩ࣑࣮ࣗࣞࢩࣙࣥࢆᐇ⾜ࡋ㸪NMRᵓ㐀ࡢ᳨ドࡶ⾜ࡗࡓ㸬࠙ ᐇ㦂ࠚGRB2ヨᩱ࡜ࡋ࡚ࡣ㸪2ࡘࡢCysṧᇶࢆ⨨᥮ࡋࡓGRB2(C32S/C198A)ࢆ⏝࠸㸪NMR
13

15

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15

EGFR࠾ࡼࡧSOS1⏤᮶ࡢ࣌ࣉࢳࢻᏑᅾୗ࡛⾜ࡗࡓ㸬 C/ Nᆒ୍ᶆ㆑ヨᩱ࡟ຍ࠼࡚㸪 H C/ Nᶆ㆑
ヨᩱࡶㄪ〇ࡋ㸪୺㙐1H/13C/15N᰾࠾ࡼࡧഃ㙐13Cȕ᰾ࡢᖐᒓࡢࡓࡵ࡟㸪HN(CA)CBࡸHN(COCA)CB࡞࡝ 6 ✀ ࡢ TROSY ᆺ 3D ୕ 㔜 ඹ 㬆 NMR ᐇ 㦂 ࢆ ⾜ ࡗ ࡓ 㸬 ࡲ ࡓ 㸪 ഃ 㙐 1H/13C ᰾ ࡢ ᖐ ᒓ ࡢ ࡓ ࡵ ࡟ 㸪
HBHA(CBCACO)NH㸪HCCH-TOCSY࡞࡝ࡢᐇ㦂ࢆ㸪NOE᝟ሗࡢゎᯒࡢࡓࡵ࡟㸪3D 13C-separated
NOESY㸪15N-separated NOESYࢆᐃࡋࡓ㸬ឤᗘࡸศゎ⬟ࡢపࡉ࠿ࡽᖐᒓࡀ㞴ࡋ࠸SH2ࢻ࣓࢖ࣥࡸ

࣮ࣜࣥ࢝㒊఩ࡢ࢔࣑ࣀ㓟࡟ࡘ࠸࡚ࡣ㸪࢔࣑ࣀ㓟㑅ᢥⓗLys㸪Leu㸪Trpᶆ㆑ヨᩱ㸪࠾ࡼࡧ࣓ࢳࣝᇶ㑅ᢥᶆ㆑ヨᩱࢆㄪ〇ࡋ㸪ྛ✀NMRࢆᐃࡍࡿࡇ࡜࡛ᖐᒓ᝟ሗࢆ⿵ࡗࡓ㸬RDCࡣ㸪PF1 Phageࢆ⏝࠸࡚㓄ྥࡉࡏࡓヨᩱ࡟ࡘ࠸࡚㸪IPAP-HSQC

ᐃࢆ⾜ࡗ࡚ồࡵࡓ㸬PREࡣ㸪Cysṧᇶࢆ᪂ࡓ࡟ᑟධࡋࡓ3✀ࡢኚ␗యA13C㸪S137C㸪N208Cࢆㄪ〇ࡋ㸪ࢫࣆࣥࣛ࣋ࣝ࡜ࡋ࡚MTSLࢆ⤖ྜࡉࡏࡿࡇ࡜࡛ྲྀᚓࡋ
ࡓ㸬PRE㸪RDC⏤᮶ࡢ㊥㞳࣭ゅᗘ᝟ሗ࡟ຍ࠼㸪
NOE⏤᮶ࡢ㏆㊥㞳᝟ሗ㸪࠾ࡼࡧ໬Ꮫࢩࣇࢺ್
࠿ࡽ᥎ᐃࡉࢀࡓ஧㠃ゅᣊ᮰᝟ሗࢆ฼⏝ࡋ㸪❧యᵓ㐀ィ⟬ࢯࣇࢺ࢙࢘࢔CYANA࡟ᐇ⿦ࡋࡓ
multi-state❧యᵓ㐀ィ⟬ࢆ⾜ࡗࡓ㸬࠙⤖ᯝ࡜ᒎᮃࠚ ඛ⾜◊✲ࡢᖐᒓ⤖ᯝ[4]ࡶཧ
↷ࡋ࡚㸪3D NMRࢫ࣌ࢡࢺࣝࢆゎᯒࡋࡓ⤖ᯝ㸪
⣙84㸣ࡢ୺㙐NMRࢩࢢࢼࣝࡢᖐᒓ࡟ᡂຌࡋ
ࡓ㸬⥆ ࠸ ࡚ 㸪 PREࡢᐃ ⤖ ᯝ (Fig.1)࠿ ࡽ 㸪

MTSLࡢ ⤖ ྜ 㒊 ఩ ࢆ ୰ ᚰ ࡟ 㸪」 ᩘ ࡢ 㡿 ᇦ ࡛PRE࡟ ࡼ ࡿ ࣆ ࣮ ࢡ ᙉ ᗘ ࡢ ῶ ⾶ ࡀ ほࡉࢀࡓ 㸬 ྲྀ ᚓ ࡋ ࡓ ᝟ ሗ ࢆ ⏝ ࠸ ࡚ multi-state❧య)LJ 5HVLGXH UHVROYHG 105 VLJQDO LQWHQVLW\ UDWLRGHULYHG IURP 35( PHDVXUHPHQWV D $& PXWDQW
E 6&PXWDQW F 1&PXWDQW G 7KH35(V
FDXVHG E\ 076/FRQMXJDWLRQ WR *5% 1& DUHPDSSHGRQWKH*5%VWUXFWXUHᵓ㐀ィ ⟬ ࢆ ⾜ ࡗ ࡓ ⤖ ᯝ 㸪 ᚓ ࡽ ࢀ ࡓ ࢔ ࣥ ࢧࣥ ࣈ ࣝ ᵓ 㐀 ࡣ 㸪 3ࡘ ࢻ ࣓ ࢖ ࣥ ࡢ ┦ ᑐ 㓄 ⨨ࡀ⤖ᬗᵓ㐀࡜ࡣ኱ࡁࡃ␗࡞ࡗ࡚࠸ࡓ
(Fig.2)㸬 ࡇ ࡢ ⤖ ᯝ ࠿ ࡽ 㸪 ⁐ ᾮ ≧ ែ ࡛ ࡣ ⤖ᬗ୰࡜ࡣ␗࡞ࡿࢻ࣓࢖ࣥ㛫┦ᑐ㓄⨨ࢆྲྀ ࡿ ࡇ ࡜ ࡀ ᫂ ࡽ ࠿ ࡜ ࡞ ࡗ ࡓ 㸬⌧ ᅾ 㸪PCS᝟ሗ ࡢ ྲྀ ᚓ ࡶ ヨ ࡳ ࡚ ࠾ ࡾ 㸪SAXSࡸ DLS㸪MDࢩ࣑࣮ࣗࣞࢩࣙࣥࡢ⤖ᯝ࡜ྜࢃࡏ࡚ゎᯒࢆ㐍ࡵࡿࡇ࡜࡛㸪⁐ᾮ୰࡛ࡢࡼࡾヲ⣽࡞❧యᵓ㐀ゎᯒࢆ┠ᣦࡍ㸬࠙ཧ⪃ᩥ⊩ࠚ[1] Maignan, S. et al., Science, 1995,)LJ D  *5% HQVHPEOH VWUXFWXUHV FDOFXODWHG E\PXOWLVWDWH VWUXFWXUH FDOFXODWLRQ E  *5% FU\VWDOVWUXFWXUH E\ ; UD\ 3'%*5,  7KH GRPDLQRULHQWDWLRQRIWKHHQVHPEOHVWUXFWXUHVLVGLIIHUHQWIURPWKHFU\VWDOVWUXFWXUH

268, 291-293; [2] Yuzawa, S. et al., J. Mol. Biol, 2001, 306, 527-537; [3] Chung, JK. et al., Biophys. J, 2021,
120, 1257-1265; [4] Yuzawa, S. et al., J. Biomol. NMR, 2003, 27, 185-186.

－ 287 －

P69

㨶㢮࡬ࡢ࣐࢖ࢡࣟࣉࣛࢫࢳࢵࢡᦤ㣵࡟࠾ࡅࡿ௦ㅰࣉࣟࣇ࢓࢖ࣝᏳᐃᛶホ౯‫ۑ‬ᯇỌ୍ኴ1㸪ᆏ⏣◊஧2㸪⳥ᆅ῟1,2,3
1ᶓ὾ᕷ❧኱Ꮫ኱Ꮫ㝔 ⏕࿨་⛉Ꮫ◊✲⛉ࠊ 2≉ᐃᅜ❧◊✲㛤Ⓨἲே⌮໬Ꮫ◊✲ᡤ ⎔ቃ㈨※⛉Ꮫ◊✲ࢭࣥࢱ࣮ࠊ3ྡྂᒇ኱Ꮫ኱Ꮫ㝔 ⏕࿨㎰Ꮫ◊✲⛉

Evaluation of metabolic profile stability in fishes upon microplastics feeding‫ۑ‬Itta Matsunaga1, Kenji Sakata2, Jun Kikuchi1,2,3
1

Graduate School of Medical Life Science, Yokohama City University

2

RIKEN Center for Sustainable Resource Science3

Graduate school of Bioagricultural Sciences, Nagoya University
In recent years, the discharge of microplastics into rivers and oceans has been pointed out. Previously

reported studies in environmental toxicology and other fields have been hypothesis-driven studies using
vertebrate and invertebrate animals based on the assumption of biological effects, and there are not many
examples of data-driven studies without hypotheses. In this study, we prepared several types andconcentrations of feed containing microplastics and fed them to fish, and evaluate NMR metabolic profiles
mainly in feces, which can be sampled noninvasively and simply, as well as in fish meat samples after the
test. In doing so, we completely discarded the hypothesis of "biological effects" that is often seen in
environmental toxicology and attempted to create stability indices using data-driven approaches such asenergy landscape analysis.
࠙⫼ᬒ࣭┠ⓗࠚ࣐࢖ࢡࣟࣉࣛࢫࢳࢵ
ࢡ(MP)ࡣ୍⯡ⓗ࡟5 mm௨ୗࡢࣉࣛࢫ
ࢳࢵࢡ⢏Ꮚ࡜ᐃ⩏ࡉࢀࠊ໬⢝ရࡸࢫࢡࣛࣈ๣࡞࡝࡟౑⏝ࡉࢀࡿ࣐࢖ࢡࣟ
ࣅ࣮ࢬ࡜⎔ቃ୰࡟ὶฟࡋࡓࣉࣛࢫࢳࢵࢡ〇ရࡀ⣸እ⥺ࠊ⇕ࠊ㢼Ἴࡢᙳ㡪࡟ࡼࡾ⣽∦໬ࡋࡓࡶࡢࡀ࠶ࡿ[1]ࠋ
MPࡣἙᕝ࣭ᾏὒࢆྵࡴ඲⌫ⓗ࡞ศᕸࢆ♧ࡋ࡚࠾ࡾ[2]ࠊື≀ࣉࣛࣥࢡࢺ
ࣥࠊ㨶㢮[1]ࠊ㫽㢮ࡑࡋ့࡚ங㢮ࢆྵࡴỈ⏕⏕≀ࡢయෆ࠿ࡽࡶ᳨ฟࡉࢀ࡚
࠾ࡾࠊ⏕ែ⣔࡬ࡢᙳ㡪ࡀᏑᅾࡍࡿ࡜
࠸࠺௬ᐃࡢୗ࡛◊✲ࡉࢀ࡚ࡁࡓɽࡋ
࠿ࡋ⎔ቃẘᛶᏛ➼ࡢ᪤ሗ◊✲ࡣࠊ⏕యᙳ㡪ࢆ๓ᥦ࡜ࡋࡓ⬨᳝࣭↓⬨᳝ື

Fig. 1. Experimental scheme of this study.

≀ࢆ⏝࠸ࡓ௬ㄝ㥑ືᆺ◊✲࡛ࠊ௬ㄝ↓ࡋࡢࢹ࣮ࢱ㥑ືᆺ◊✲౛ࡣከࡃ࡞ࡃࠊࡲࡓ⌧ᐇࡢ⎔ቃ࡛ᐃࡉࢀࡓ࣐࢖ࢡࣟࣉࣛࢫࢳࢵࢡ⃰ᗘ࡜㞳ࢀࡓ᮲௳࡛ࡢ⏕య࡬ࡢᙳ㡪ࢆ᳨ウࡋ࡚࠸ࡿࡶࡢࡀ࡯࡜ࢇ㠀౵くࢧࣥࣉࣜࣥࢢࠊࢹ࣮ࢱ㥑ືᆺゎᯒࠊ࢚ࢿࣝࢠ࣮ᆅᙧゎᯒࠐࡲࡘ࡞ࡀ࠸ࡗࡓࠊࡉ࠿ࡓࡅࢇࡌࠊࡁࡃࡕࡌࡹࢇ

－ 288 －

࡝࡛࠶ࡿ[3]ࠋࡑࡇ࡛ᮏ◊✲࡛ࡣ」ᩘ✀㢮ࡢ࣐࢖ࢡࣟࣉࣛࢫࢳࢵࢡࢆྵࡴ㣵ࢆ␗࡞ࡿ㨶✀࡟୚࠼ࠊ㠀౵くⓗ࠿ࡘ⡆᫆ⓗ࡟ࢧࣥࣉࣜࣥࢢྍ⬟࡞⣅౽ࢆ୰ᚰ࡟ࠊࡉࡽ࡟ヨ㦂ᚋࡢ㨶⫗ヨᩱࡶྵࡵ࡚
NMRࡢ௦ㅰࣉࣟࣇ࢓࢖ࣝࢆホ౯ࡍࡿࠋࡇࡢ㝿࡟⎔ቃẘᛶᏛ࡛ᩓぢࡉࢀࡿࠕ⏕యᙳ㡪ࡀ࠶ࡿࠖ௬
ㄝࢆ᏶඲࡟ྲྀࡾᡶ࠸ࠊ࢚ࢿࣝࢠ࣮ᆅᙧゎᯒ➼ࡢࢹ࣮ࢱ㥑ືᆺ࢔ࣉ࣮ࣟࢳ࡟ࡼࡾࠊᏳᐃᛶᣦᶆ໬ࢆ
ヨࡳࡿࠋ࠙᪉ἲࠚ ࢝ࢧࢦ࡟࣏࢚ࣜࢳࣞࣥࢸࣞࣇࢱ࣮ࣛࢺ(PET)⃰ᗘ0.1 %ࡢΰྜ㣫ᩱ࡜ࢥࣥࢺ࣮ࣟࣝ㣫ᩱ(ࣉࣛࢫࢳࢵࢡࢆྵࡲ࡞࠸)ࢆᦤ㣵ࡉࡏࠊ࣓ࣂࣝ࡟ࡣ⏕ศゎᛶࣉࣛࢫࢳࢵࢡࠊࡍ࡞ࢃࡕ࣏ࣜ࢝ࣉࣟ
ࣛࢡࢺࣥ(PCL)ࠊ࣏࢚ࣜࢳࣞࣥࢧࢡࢩࢿ࣮ࢺ(PES)ࠊ࣏ࣜࣄࢻࣟ࢟ࢩ㓗㓟(PHB)ࢆࡑࢀࡒࢀ⃰ᗘ
0.1 %࡛ΰྜࡉࡏࡓ3✀㢮ࡢ㣫ᩱ࡜ࢥࣥࢺ࣮ࣟࣝ㣫ᩱ(ࣉࣛࢫࢳࢵࢡࢆྵࡲ࡞࠸)ࢆᦤ㣵ࡉࡏࠊ⣅౽ヨᩱࢆ᥇ྲྀࡋࡓࠋࡑࢀࢆ෾⤖஝⇱ࡋࡓᚋ⢊○ࡋࠊKPi/D2O࡟⁐࠿ࡋᚓࡽࢀࡓୖΎࡳࢆNMRࢧࣥࣉࣝ࡜ࡋࠊ⁐ᾮNMR(700 MHz)ࡢ2D-Jresィ ࡟ࡼࡾỈ⁐ᛶపศᏊ⩌ࢆィ ࡋࡓࠋNMRࢫ࣌ࢡࢺࣝ
ࢆᩘ್໬ࡋࠊ⤫ィィ⟬ࢯࣇࢺR࡟ࡼࡾ୺ᡂศศᯒ(PCA)ࢆ⾜࠸ࠊ㨶㢮࡟࠾ࡅࡿ㣫ᩱ࠾ࡼࡧMPධຊࡢฟຊᛂ⟅ࢆホ౯ࡋࡓࠋ᪤▱⃰ᗘࡢPCLヨᩱࢆࢡ࣒ࣟࣟ࣍ࣝ⁐፹࡛ᢳฟࡋࠊ700 MHzࡢNMR࡟ࡼࡾᚓࡽࢀࡓࢩࢢࢼࣝᙉᗘࢆ⏝࠸᳨࡚㔞⥺ࢆసᡂࡋࡓࠋ⣅౽ヨᩱࡶࢡ࣒ࣟࣟ࣍ࣝ⏬ศࡢNMRࢩࢢࢼࣝࢆྲྀᚓࡋࠊసᡂࡋࡓ᳨㔞⥺࠿ࡽ⣅౽୰࡟࠾ࡅࡿࣉࣛࢫࢳࢵࢡ⃰ᗘࢆ⟬ฟࡋࡓࠋ࠙⤖ᯝ࣭⪃ᐹࠚ࢝ࢧࢦࡢ
0.1 %PETᦤ㣵ᐇ㦂࡟࠾ࡅࡿ⣅౽௦ㅰ≀ࡢỈ⁐ᛶపศᏊ⩌ࢹ࣮ࢱࢆ౑⏝ࡋ࡚PCAࢆ⾜ࡗࡓ⤖ᯝࠊPC1㍈ࡢṇࡢ᪉ྥ࡟PETᦤ㣵᫬ࡢ௦ㅰࣉࣟࣇ࢓࢖ࣝࡀ
ศᕸࡍࡿഴྥࡀ࠶ࡗࡓ(Fig.
2a)ࠋ࣓ࣂࣝࡢ0.1 %PCLࠊ
PESࠊPHBᦤ㣵ᐇ㦂࡟࠾ࡅࡿ
PCA⤖ᯝࡣࢥࣥࢺ࣮ࣟࣝ㣫ᩱ
࡜MPΰྜ㣫ᩱ࡜࡛ࡣ࡯࡜ࢇ࡝
ᕪ␗ࡀ࡞࠿ࡗࡓ(Fig. 2b)ࠋࡲࡓ

Fig. 2. Profiles of water-soluble fecal components evaluated by PCA.
(a) Feeding 0.1 % PET, (b) Feeding 0.1 % PCL, PES and PHB.

MP᳨ฟ࡟㛵ࡋ࡚ࠊPCLᦤ㣵ᮇ㛫୰ࡣ⣅౽࠿ࡽ㧗࠸⃰ᗘ࡛PCLࡀ᳨ฟࡉࢀ࡚࠸ࡿࡀࠊࢥࣥࢺ࣮ࣟࣝ
ᦤ㣵ᮇ㛫୰ࡣ᳨ฟࡉࢀ࡞࠿ࡗࡓࠋῐỈ㨶࡬ࡢ10 m௨ୗࡢMP᭚㟢ᐇ㦂࡛ࡣ⏕య⤌⧊࡬ࡢ⵳✚ሗ࿌ࡀ࠶ࡿࡀ[4]ࠊMPࡢ┤ᚄࡀ150~355 m࡞ࡽ⏕య⤌⧊࡬ࡢ⵳✚ࡣ࡞ࡃࠊ⣅౽࡜ࡋ࡚᤼ฟࡉࢀࡿྍ⬟ᛶࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋᮏ఍࡛ࡣࡇࢀࡽࡢ⤖ᯝ࡟ຍ࠼ࠊ⣅౽୰࡟࠾ࡅࡿ௦ㅰ≀ࡢ࢚ࢿࣝࢠ࣮ࣛࣥ
ࢻࢫࢣ࣮ࣉゎᯒ࡟ࡼࡿ⏕≀௦ㅰࡢᏳᐃᛶホ౯ࡶሗ࿌ࡍࡿࠋ
References[1] Tanaka, K., Takada, H. Microplastic fragments and microbeads in digestive tracts of planktivorous fishfrom urban coastal waters. Sci Rep 6, 34351 (2016).
[2] Eriksen M, Lebreton LCM, Carson HS, Thiel M, Moore CJ, Borerro JC, et al. (2014) Plastic Pollution in
the World's Oceans: More than 5 Trillion Plastic Pieces Weighing over 250,000 Tons Afloat at Sea. PLoS
ONE 9(12): e111913.
[3] Isobe, A., Iwasaki, S., Uchida, K. et al. Abundance of non-conservative microplastics in the upper ocean
from 1957 to 2066. Nat Commun 10, 417 (2019).
[4] Safoura Abarghouei et al. (2021) Chemosphere 276,129977－ 289 －P70Y

%XOOHW'13ࢆ⏝࠸ࡓࣆࣝࣅࣥ㓟ࡢ㓝⣲཯ᛂᐇ㦂‫ۑ‬ᮃ᭶భ⣖㸪῝⃝㞙᰿᮶ㄔ໭ᕝ຾ᾈ㤶ᕝ᫭ᚨ
኱㜰኱Ꮫ࣭኱Ꮫ㝔ᇶ♏ᕤᏛ◊✲⛉኱㜰኱ᏛඛᑟⓗᏛ㝿◊✲ᶵᵓ㔞Ꮚ᝟ሗ࣭㔞Ꮚ⏕࿨◊✲ࢭࣥࢱ࣮
㔞Ꮚ⛉Ꮫᢏ⾡◊✲㛤Ⓨᶵᵓ 467 

Enzyme reaction experiment of pyruvic acid with bullet DNPżYuki Mochizuki1, Jun Fukazawa2, Makoto Negoro2.3, Masahiro Kitagawa1.2, Akinori Kagawa1.2
1Graduate School of Engineering Science, Osaka University

2

Center for Quantum Information and Quantum Biology, Institute for Open and Transdisciplinary Research

Initiatives, Osaka University,
3Institutefor Quantum Life Science, National Institutes for Quantum and Radiological Science andTechnology
Pyruvic acid plays a significant role in biology. It is known that the production of lactate from pyruvic acidby lactate dehydrogenase (LDH) is more accelerated in cancer cells than in normal cells. A dissolution
DNP(d-DNP) system is used to observe the enzymatic reaction in real-time and offers hyperpolarized
solution NMR. Recently, a new d-DNP instrument called bullet-DNP has been developed. The key
advantages are that transfer of samples in bullet DNP is faster than in conventional d-DNP systems, and thesystem does not require a large amount of solvent for dissolution. However, real-time enzymatic reaction
experiments using the bullet DNP apparatus have not yet been performed. Using our developed bullet-DNP
apparatus, we showed time-resolved, enhanced solution 13C-NMR spectra of enzymatic reaction frompyruvic acid to lactate by LDH.
㹙ᗎㄽ㹛㏆ᖺࠊᴟప ୗ࡛'13࡟ࡼࡗ࡚㧗೫ᴟ໬ࡋࡓࢧࣥࣉࣝࢆ⁐ゎࡋࠊ⁐ᾮ105ࢆ ᐃࡍࡿ⁐ゎ'13>@ࡢ㛤ⓎࡀάⓎ࡟⾜ࢃࢀ࡚࠸ࡿࠋ⁐ゎ'13࡟ࡼࡗ࡚పឤᗘ᰾࡛࠶ࡿ&ࢫࣆࣥࡢ㓝⣲཯ᛂࡢࣜ࢔ࣝࢱ࢖࣒ィ ࡀᐇ⌧ࡉࢀ࡚࠸ࡿࠋࡑࡢ࡞࠿࡛ࡶࣆࣝࣅࣥ㓟ࡣࠊࡀࢇ⣽⬊࡛ࡣங㓟⬺Ỉ⣲㓝⣲ /'+ ࡟ࡼࡿங㓟ࡢ⏕ᡂࡀṇᖖ⣽⬊࡟ẚ࡭ಁ㐍ࡉࢀ࡚࠸ࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿ࡞࡝⏕యෆ࡟࠾࠸࡚㠀ᖖ࡟㔜せ࡞ᙺ๭ࢆᢸࡗ࡚࠸ࡿ>@ࠋᡃࠎࡣ⁐ゎ'13ࡢ࡞࠿࡛ࡶࠊbullet-DNP[3]࡜࿧ࡤࢀࡿ⿦⨨ࡢ㛤Ⓨ࡟ྲྀࡾ⤌ࢇ࡛࠸ࡿࠋ㏻ᖖࡢ⁐ゎDNP࡛ࡣࠊᴟప ୗ࡛ࢧࣥࣉࣝࢆ⁐ゎࡋࠊ⁐ᾮ㌿㏦ࢆ⾜࠺ࡢ࡟ᑐࡋ
࡚ࠊbullet-DNP࡛ࡣᅛయ≧ࡢࢧࣥࣉࣝࢆ㌿㏦ࡋࠊᐊ ୗ࡛⁐ゎࢆ⾜࠺ࠋࡑࡢࡓࡵ㏻ᖖࡢ⁐ゎD13⿦⨨࡜ẚ㍑ࡍࡿ࡜ࢧࣥࣉࣝࡢ㧗㏿࡞㌿㏦࡜ᑡ࡞࠸⁐፹࡛ࡢ㧗೫ᴟ໬ࢧࣥࣉࣝࡢ⁐ゎࡀྍ⬟࡜࡞ࡗ
࡚࠸ࡿ>@ࠋ≉࡟ࢧࣥࣉࣝࡢᕼ㔘㔞ࡀᑡ࡞࠸ࡇ࡜ࡣࠊ㧗౯࡞ࣛࢪ࢝ࣝࡸྠ఩యศᏊࡢ౑⏝㔞ࢆῶࡽࡏࡿࡇ࡜࡜ྠ➼࡛࠶ࡾࠊ㔜せ࡛࠶ࡿ࡜⪃࠼࡚࠸ࡿࠋࡋ࠿ࡋEXOOHW'13⿦⨨ࢆ⏝࠸ࡓࣜ࢔ࣝࢱ࢖
࣒࡞㓝⣲཯ᛂᐇ㦂ࡣᮍࡔ⾜ࢃࢀ࡚࠸࡞࠸ࠋࡑࡇ࡛ᮏ◊✲࡛ࡣᡃࠎࡀ㛤ⓎࡋࡓEXOOHW'13⿦⨨ࢆ⏝࠸࡚ྠ఩య⨨᥮ࡋࡓ&ࣆࣝࣅࣥ㓟ࡢ/'+࡟ࡼࡿங㓟࡬ࡢ㓝⣲཯ᛂࡢࣜ࢔ࣝࢱ࢖࣒ ᐃࢆ⾜ࡗࡓࠋEXOOHW'13ࠊࣆࣝࣅࣥ㓟ࠊ/'+‫ࡁ࠺ࡺࡁ࡙ࡕࡶۑ‬㸪ࡩ࠿ࡊࢃࡌࡹࢇ㸪ࡡࡈࢁࡲࡇ࡜㸪ࡁࡓࡀࢃࡲࡉࡦࢁ㸪࠿ࡀࢃ࠶ࡁࡢࡾ
－ 290 －

㹙ᐇ㦂⤖ᯝ㹛ࢧࣥࣉࣝࡣ೫ᴟ※࡜࡞ࡿ%'3$ࢆP0ῧຍࡋࡓࢫࣝ࣍ࣛࣥ࡜೫ᴟᑐ㇟ศᏊࡢ&ࣆࣝࣅࣥ㓟ࢆࡢ๭ྜ࡛ΰࡐࡓࡶࡢࢆ⏝࠸ࡓࠋࡇࡢࢧࣥࣉࣝࢆᾮయ❅⣲࡟⁲ୗࡋࠊ࢞ࣛࢫ≧ࡢࣅ࣮ࢬ 㹼ȝO ࢆస〇ࡋࠊࣂࣞࢵࢺ࡜࿧ࡤࢀࡿ෇⟄≧ࡢࢸࣇࣟࣥᐜჾ࡟ධࢀ࡚㧗೫ᴟ໬ࢆ⾜ࡗࡓࠋ .ࠊ
 7࡛ࣛࢪ࢝ࣝࡢ⃰ᗘࠊ࣐࢖ࢡࣟἼ࿘Ἴᩘ࠾ࡼࡧᤲᘬᖜ࡞࡝ࢆ᭱㐺໬ࡋࠊ'13ࢆ⾜ࡗࡓ⤖ᯝࠊ&ࢫࣆࣥࡢ೫ᴟ⋡⣙ࢆ㐩ᡂࡋࡓࠋḟ࡟ࡇࡢ㧗೫ᴟ໬ࡋࡓࢧࣥࣉࣝࡢ㌿㏦ࠊ⁐ゎࢆ⾜ࡗࡓࠋᅛయ≧ࡢࢧࣥࣉࣝࡀධࡗࡓࣂࣞࢵࢺࢆ㧗ᅽ࣒࣊ࣜ࢘࢞ࢫ࡛'13⏝㉸ఏᑟ☢▼࠿ࡽᾮయ105⏝㉸ఏᑟ☢
▼ࡲ࡛㌿㏦ࡍࡿ )LJ ࠋ㌿㏦୰ࡢ⦆࿴ࢆᢚไࡍࡿࡓࡵ࡟☢ሙࢺࣥࢿࣝࢆ⏝࠸࡚࠸ࡿࠋ㌿㏦ᚋࠊ☢ሙ୰ᚰ࠿ࡽ⣙FPୖ࡟࠶ࡿ⁐፹ᐜჾ୰࡛ࠊOࡢ⇕Ỉࢆ⏝࠸࡚ࢧࣥࣉࣝࢆ⁐ゎࡍࡿࠋࡉࡽ࡟
㉸ఏᑟ☢▼୰ᚰ࡟㌿㏦ࡋࠊࡑࡢᚋ105 ᐃࢆ⾜࠺ࠋᮏ◊✲࡛స〇ࡋࡓEXOOHW'13⿦⨨࡛ࡣ⣙⛊ࡢヨᩱࡢ㧗㏿㌿㏦ࡀ⾜࠼ࡿࠋEXOOHW'13࡟ࡼࡿ㧗೫ᴟ໬ࡉࢀࡓࣆࣝࣅࣥ㓟ࡢ⁐ᾮ୰࡛ࡢ&ࢫ࣌ࢡࢺࣝಙྕᙉᗘࡣ⇕ᖹ⾮᫬࡜ẚ㍑ࡋ࡚᭱኱࡛ಸ࡜࡞ࡾࠊ೫ᴟ⋡ࡣ࡛࠶ࡗࡓࠋ
EXOOHW'13࡟ࡼࡿ㓝⣲཯ᛂࡢࣜ࢔ࣝࢱ࢖࣒ィ ࡛ࡣ࠶ࡽ࠿ࡌࡵヨ㦂⟶ෆ࡟ධࢀ࡚࠾࠸ࡓ㓝⣲⁐ᾮ࡜㧗೫ᴟ໬ࡉࢀࡓࢧࣥࣉࣝࢆ⁐ゎࡋࡓ⁐ᾮࢆΰࡐࡿࡇ࡜࡛㓝⣲཯ᛂࢆᘬࡁ㉳ࡇࡍࠋ㓝⣲⁐ᾮࡣ/ங㓟ࢹࣄࢻࣟࢤࢼ࣮ࢮ ࢘ࢩᚰ⮚⏤᮶ /'+ ࠊș1$'+ࠊ࢘ࢩ⾑Ύ࢔ࣝࣈ࣑ࣥ %6$ ࢆOࡢࣜࣥ㓟⦆⾪⏕⌮㣗ሷỈ 3%6 ࡟⁐࠿ࡋࡓࡶࡢ࡛࠶ࡿࠋ㌿㏦ࡉࢀ࡚ࡁࡓࢧࣥࣉࣝࢆ⁐࠿ࡍ⁐፹࡟ࡣOࡢࣜࣥ㓟⦆⾪ᾮࢆ⏝࠸ࡓࠋEXOOHW'13ࢆ⏝࠸ࡓࢹࣔࣥࢫࢺ࣮ࣞࢩ࡛ࣙࣥࡣࠊࣆࣝࣅࣥ㓟ࡢ㓝⣲཯ᛂ࡟ࡼࡗ࡚⏕ᡂࡉࢀࡓங㓟ࡢಙྕࢆほ ࡍࡿࡇ࡜ࡀ࡛ࡁࡓ㸦)LJ ࠋࡇࡢ⤖ᯝ࠿ࡽࢧࣥࣉ
ࣝ࡜㓝⣲ࢆΰࡐ࡚࠿ࡽᾮయ105࡛ಙྕࢆほ ࡍࡿࡲ࡛ࡢ▷࠸ࢱ࢖࣒ࢫࢣ࣮࡛ࣝࡶ㓝⣲཯ᛂࢆ㉳ࡇࡋ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡗࡓࠋᐊ 105ࡢ&ࢫࣆࣥࡢ ᐃ࡛ࡣឤᗘࡀపࡃࠊ✚⟬ࡍࡿᚲせࡀ࠶ࡾࠊ▷࠸ࢫࢣ࣮࡛ࣝࡢ㓝⣲཯ᛂࡢᵝᏊࢆほ ࡍࡿࡇ࡜ࡀ࡛ࡁ࡞࠸ࠋࡋ࠿ࡋEXOOHW'13ࢆ⏝࠸ࡿࡇ࡜࡛ࣜ
࢔ࣝࢱ࢖࣒࡛ࡢ㓝⣲཯ᛂࢆほ ࡍࡿࡇ࡜ࡀྍ⬟࡜࡞ࡗࡓࠋ

Fig. 1. Schematic diagram of our bullet DNP.

Fig. 2. Time-resolved enhanced solution
13

C-NMR spectra for pyruvate acidacquired with a time interval of 1 s.

References[1] Ardenkjær-Larsen J.H. et al., PNAS, 100, 18, 10158-10163 (2003)[2] Nobu Oshima et al., ScienceDirect, 30, 6, 1798-1810 (2020)[3] Karel KouĜil et al., Nature com., 10, 1733 (2019)－ 291 －

P71࣌ࣟࣈࢫ࢝࢖ࢺᆺ㓟❅໬≀ࡢ14NᅛయNMRࡢ෌᳨ウ‫ۑ‬㔝⏣Ὀᩯ㸪▼஭ᱜᏊ1, ᪂ᮌ⪽ኴ1, ᪥㒊㞝ኴ1, 㫟ῲ཭἞2, ➉⭜Ύ஀⌮11ி㒔኱Ꮫ኱Ꮫ㝔࣭⌮Ꮫ◊✲⛉2໭ᾏ㐨኱Ꮫ኱Ꮫ㝔࣭ᕤᏛ◊✲⛉

Revisiting 14N solid-state NMR of perovskite-type oxynitrides‫ۑ‬Yasuto Noda1, Sakurako Ishii1, Souta Shinki1, Yuta Hibe1, Yuji Masubuchi2, Kiyonori Takegoshi1
1Division of Chemistry, Graduate School of Science, Kyoto University

2

Division of Applied Chemistry, Faculty of Engineering, Hokkaido University
We re-examined 14N solid-state NMR of BaTaO2N as a representative perovskite-type oxynitride, andfound a wide-line spectrum over 2 MHz in contrast to the previous works reporting a single narrow peak at
ca. 270 ppm. We conclusively assign the latter to the residual nitrogen gas, which can be removed by heat
treatment. The true 14N NMR spectrum, revealed with both a number of frequency-incremented QCPMG
experiments and a long accumulation delay time exceeding 400 s, showed a profile of a slightly asymmetric
14N quadrupolar interaction, indicating that the nitrogen atoms are off the Ta-N-Ta line in the crystal.

࣌ࣟࣈࢫ࢝࢖ࢺᆺ㓟❅໬≀ࡣ㓟໬≀࡛ࡣྲྀࡾᚓ࡞࠸ከᵝ࡞ᒁᡤᵓ㐀ࢆᐇ⌧࡛ࡁࠊ᪂ࡋ࠸≀㉁⩌࡜ࡋ࡚ὀ┠ࡀ㞟ࡲࡗ࡚࠸ࡿ[1]ࠋ≀ᛶࡸᶵ⬟ࡢ⌮ゎ࡟ࡣᵓ㐀ゎᯒࡀḞ࠿ࡏ࡞࠸ࡀࠊᚑ᮶ࡢ㓟໬≀࡛ࡣᴟຊ࡞ᵓ㐀ゎᯒᡭἲ࡛࠶ࡿ㹖⥺ᅇᢡἲࡣ࢔ࢽ࢜ࣥࡀྠࡌ㛢Ẇᵓ㐀ࢆ࡜ࡿࡓࡵ㞴ࡋࡃࠊศගᏛⓗᡭἲࡶᚲせ࡜࡞ࡿࠋᵝࠎ࡞⤌ᡂࡢ࣌ࣟࣈࢫ࢝࢖ࢺᆺ㓟❅໬≀࡛14NᅛయNMRࡢᐃࡀ⾜ࢃࢀࡓࡀࠊ

ඹ㏻ࡋ࡚⣽࠸ಙྕࡀ1ᮏࡔࡅ270 ppm௜㏆࡟ほ ࡉࢀࡿࡢࡳ࡛ࠊᵓ㐀ࡸ⤌ᡂ࡟㕌ឤ࡛࠶ࡾࠊ❅⣲ࢆྵ᭷ࡋ࡚࠸ࡿ࡜࠸࠺᝟ሗ⛬ᗘࡋ࠿ᚓࡽࢀ࡚࠸࡞࠸[2–4] ࠋ௨ୖࡢⅬ࡟␲ၥࢆᣢࡕࠊᮏ◊✲࡛ࡣ඾ᆺⓗ࡞࣌ࣟࣈࢫ࢝࢖ࢺᆺ㓟❅໬≀࡜ࡋ࡚BaTaO2Nࢆ᥇⏝ࡋ14NᅛయNMRࢆ᳨ウࡋࡓࠋ
BaTaO2N⢊ᮎࢆ᪤ሗࡢᡭἲ[5]ࢆ⏝࠸࡚BaCO3࡜Ta2O5ࡢΰྜ≀㸦ࣔࣝẚ1.03ᑐ1㸧ࢆ100 mL/minࡢ࢔ࣥࣔࢽ࢔Ẽὶ୰࡛930Υ30᫬㛫ຍ⇕ᚋࠊ࢔ࣥࣔࢽ࢔㞺ᅖẼ୰࡛෭༷ࡍࡿࡇ࡜࡛ྜᡂࡋࡓࠋ඲࡚ࡢ
14

NᅛయNMRࡣ14 Tࡢ☢ሙ࡛⮬సࣉ࣮ࣟࣈ࡜Opencoreศගィࢆ⏝࠸࡚ᐇ᪋ࡋࡓࠋሷ໬࢔ࣥࣔࢽ࣒࢘

ࢆ໬Ꮫࢩࣇࢺࡢእ㒊ᶆ‽࡜ࡋ࡚⏝࠸ࡓࠋ㟼Ṇ≧ែࡢBaTaO2N⢊ᮎࡢ14N solid echo NMRࢆᚅࡕ᫬㛫0.1 s࡛ ᐃࡋࡓ࡜ࡇࢁࠊFig. 1ࡢ㯮Ⰽ⥺࡛♧ࡍࡼ࠺࡟୍ᮏࡢᑐ⛠ⓗ࡞ࣆ࣮ࢡࢆ270 ppm࡟ほ ࡋࡓࠋࣆ࣮ࢡ఩⨨ࡀ᪤ሗࡢ269.2 ppm[2]࡟ᐇ
㦂ࡢㄗᕪ⠊ᅖෆ୍࡛⮴ࡋ࡚࠸ࡿࡇ࡜࠿ࡽࠊほࡋࡓಙྕࡣࡇࢀࡲ࡛ሗ࿌ࡉࢀ࡚ࡁࡓࡶࡢ࡜ྠ୍࡛

࠶ࡿࠋࡇࡢಙྕࡀBaTaO2N⤖ᬗ㦵᱁ෆࡢ❅⣲࡟⏤᮶ࡍࡿ࠿࡝࠺࠿ಙྕᙉᗘࡢほⅬ࠿ࡽ᳨ドࡋࡓࠋ❧᪉ᬗ࡛࠶ࡿTiN3ࢆ⏝࠸࡚ྵ᭷❅⣲㔞࡜ಙྕᙉᗘࡢ㛵ಀࢆ๭ࡾฟࡋࠊBaTaO2Nࡢಙྕᙉᗘࢆ᥎ᐃ
ࡋࡓ࡜ࡇࢁࠊྵ᭷❅⣲㔞࠿ࡽィ⟬ࡉࢀࡿ್ࡢ5.0 %࡟࡜࡝ࡲࡗࡓࠋࡑࡢ⣽࠸⥺ᖜ࡜12 ms࡜࠸࠺㏿࠸⦪⦆࿴᫬㛫࠿ࡽࠊಙྕࡣBaTaO2N࡛ࡣ࡞ࡃ㧗࠸㐠ືᛶࢆࡶࡘศᏊᛶ≀㉁࡟⏤᮶ࡍࡿ࡜᥎ᐹࡋࡓࠋ
ೃ⿵࡜ࡋ࡚ࡣࠊྜᡂ㞺ᅖẼࡢ࢔ࣥࣔࢽ࢔ศᏊ࡜ࠊBaTaO2Nࡣྜᡂᚋ࡟࢔ࣥࣔࢽ࢔㞺ᅖẼ୰࡛෭༷䝨䝻䝤䝇䜹䜲䝖ᆺ㓟❅໬≀䠈14NᅛయNMR䠈ᗈᖜ䕿䛾䛰 䜔䛩䛸䠈䛔䛧䛔 䛥䛟䜙䛣䠈䛧䜣䛝 䛭䛖䛯䠈䜂䜉 䜖䛖䛯䠈䜎䛩䜆䛱 䜖䛖䛨䠈䛯䛡䛤䛧 䛝䜘䛾䜚－ 292 －

ࡍࡿ࡜❅⣲ศᏊࡀṧ␃ࡍࡿ[5]ࡓࡵ❅⣲ศᏊࡀ⪃࠼ࡽࢀࡿࠋ࢔ࣥࣔࢽ࢔࢞ࢫ࡜Ꮩ❧❅⣲ศᏊࡢ໬Ꮫ
ࢩࣇࢺ್ࡣࡑࢀࡒࢀ-55.2 ppm [6]࡜277.9 ppm [7]࡛࠶ࡾࠊ❅⣲ศᏊࡢྍ⬟ᛶࡀ㧗࠸࡜ண᝿ࡋࡓࠋ
ᐇ㝿࡟❅⣲ศᏊࡀṧ␃ࡋ࡚࠸ࡿ࠿࡝࠺࠿ࢆ᳨ドࡍ ࡿࡓࡵ ࠊṧ␃ ❅⣲ࡢࡳ ࢆ㝖ཤ ࡍࡿ᮲ ௳ [5]࡛BaTaO2Nࡢ⇕ฎ⌮ࢆ⾜࠸ࠊྵ᭷❅⣲㔞ࡢኚ໬࡜14N
NMRಙྕࡢኚ໬ࢆ ᐃࡋࡓࠋࡑࡢ⤖ᯝࠊ❅⣲ྵ᭷㔞ࡣ3.58 wt%࠿ࡽ3.38 wt%࡜5.59 %ῶᑡࡋࠊࡉࡽ࡟
14

N NMRࡢࣆ࣮ࢡࡣᾘኻࡋࡓ㸦Fig. 1ࡢ⅊Ⰽ⥺㸧ࠋ

Fig. 1. A 14N solid-echo spectrum of BaTaO2N
powder before (black line) and after (grayline) heat treatment in N2 atmosphere.

௨ୖࡼࡾࠊࡇࢀࡲ࡛BaTaO2N࡛࠶ࡿ࡜ሗ࿌ࡉࢀ࡚
ࡁࡓಙྕࡀᐇࡣ❅⣲ศᏊ࡟ࡼࡿࡶࡢ࡜⤖ㄽࡋࡓࠋ㓟❅໬≀㦵᱁ෆ࡟Ꮡᅾࡍࡿ14N NMRࢫ࣌ࢡࢺࣝ
ࡢᐃ㔞ⓗ࡞ほ ࢆ㣬࿴௜QCPMGἲ࡟ࡼࡾヨࡳࡓࠋᐇ㦂ࣃ࣓࣮ࣛࢱࡣKNO3ࢆ⏝࠸࡚᭱㐺໬ࡋࡓࠋᚅࡕ
᫬㛫ࢆ430 sࠊ✚⟬ᅇᩘࢆ32ᅇ࡜ࡋ࡚㐃⥆ࡍࡿ࢚ࢥ࣮ࢆྲྀᚓࡋࡓࡢࡕ࡟ࣇ࣮࢚ࣜኚ᥮ࢆ⾜࠸୍ࡘࡢࢧ
ࣈࢫ࣌ࢡࢺࣝࢆᚓࡓࠋほ࿘Ἴᩘࢆ62.5 kHzࡎࡽࡍẖ࡟ࢳ࣮ࣗࢽࣥࢢ࡜ ᐃࢆ⧞ࡾ㏉ࡋࠊᚓࡽࢀࡓ
ࢧࣈࢫ࣌ࢡࢺࣝࢆ㔜ࡡྜࢃࡏ࡚Fig. 2࡟♧ࡍࡼ࠺࡞⣙2 MHz࡟ࡶཬࡪᖜᗈ࠸ࢫ࣌ࢡࢺࣝࢆᚓࡿࡇ࡜
࡟ᡂຌࡋࡓࠋT1ࡣ342 s࡛࠶ࡗࡓࠋᚓࡽࢀࡓࢫ࣌ࢡ
ࢺࣝᙧ≧ࡣࠊ⤖ᬗෆࢧ࢖ࢺࡢᑐ⛠ᛶࡀ୍㍈ᑐ⛠ᛶFig. 2. A 14N QCPMG spectrum of BaTaO2N
powder before heat treatment. The sharp
component is attributed to N2 gas.

࠿ࡽపୗࡋ࡚࠸ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋࡇࢀࡣTa-N-Taࡀ┤⥺≧࡟ぢ࠼࡚࠸ࡿXRD࡜ࡣ␗࡞ࡿ⤖ᯝ࡛࠶ࡾࠊ▷㊥㞳ⓗ࡟ࡣᑡࡋᢡࢀ᭤ࡀࡗࡓTa-N-Taࡀ୙つ๎࡟Ꮡᅾࡍࡿࡇ࡜࡟ࡼࡾࠊ㛗㊥㞳ⓗ࡞ᖹᆒᵓ㐀࡛ࡣTa-N-Taࡀ┤⥺ⓗ࡟ぢ࠼࡚࠸ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ
௨ୖࡼࡾࠊࡇࢀࡲ࡛ࡢሗ࿌࡜ࡣ␗࡞ࡾࠊ14N NMRࢫ࣌ࢡࢺࣝࡣ࣌ࣟࣈࢫ࢝࢖ࢺᆺ㓟❅໬≀ࡢࢧ࢖ࢺ᝟ሗࢆ㇏ᐩ࡟᭷ࡋ࡚࠾ࡾࠊᒁᡤᵓ㐀࡜≀ᛶ࣭ᶵ⬟࡜ࡢ┦㛵ࢆ᥈ࡿ◊✲࡬ࡢᒎ㛤ࡀᮇᚅࡉࢀࡿࠋ
ᮏ◊✲ࡣJSPS⛉◊㈝16H06439࡜16H06440 ͆᪂Ꮫ⾡㡿ᇦࠕ」ྜ࢔ࢽ࢜ࣥ໬ྜ≀ࡢ๰〇࡜᪂ᶵ⬟͇ࠖࡢຓᡂࢆཷࡅ࡚ᐇ᪋ࡉࢀࡓࠋ
References[1] H. Kageyama et al., Nat. Commun. 9, 772 (2018).
[2] T. Br㽯uniger et al., Chem. Mater. 17, 4114–4117 (2005).
[3] Y-Il Kim and Y. Park, Solid State Sci. 14, 580–582 (2012).
[4] N. Cordes et al., Eur. J. Inorg. Chem. 2018, 5019–5026 (2018).
[5] A. Hosono et al., J. Eur. Ceram. Soc. 36, 3341–3345 (2016).
[6] P. R. Srinivasan and R. L. Lichter, J. Magn. Reson. 28, 227–234 (1977).
[7] P. Garbacz et al., Chem. Phys. Lett. 699, 194–198 (2018).

－ 293 －

P72

13C࠾ࡼࡧ15Nᶆ㆑5-࢔࣑ࣀࣞࣈࣜࣥ㓟ࡢྜᡂ࡜NMRゎᯒ‫ۑ‬㟷ᒣὒྐ㸪㣤ሯభ௓㸪ỌỤᓠᖾ㸪ᗈ℩ ౡ2㸪୕ᓥṇつ
1ᮾி⸆⛉኱Ꮫ࣭⸆Ꮫ㒊
2㇏ᶫᢏ⾡⛉Ꮫ኱Ꮫ࣭኱Ꮫ㝔ᛂ⏝໬Ꮫ࣭⏕࿨ᕤᏛ⣔

Synthesis of 13C- and/or 15N-labeled 5-aminolevulinic acids and their NMR analyses‫ۑ‬Hiroshi Aoyama1, Yusuke Iizuka1, Takayuki Nagae1, Yuu Hirose2, Masaki Mishima1
1

School of Pharmacy, Tokyo University of Pharmacy & Life Sciences2

Department of Applied Chemistry and Life Science, Toyohashi University of Technology
To analyze the bilin-binding domain of the cyanobacterial chromatic acclimation sensor RcaE in thegreen-absorbing photoproduct state by NMR, we examined the synthesis of labeled 5-aminolevulinic acid
(5-ALA), which leads to labeling with stable isotopes of bilin chromophore.
As a result of investigating the synthesis of unlabeled 5-ALA that protects both the C-terminal and the
N-terminal, it was found that Pd-catalyzed Fukuyama coupling reaction between glycine thioester andorganozinc reagent is effective. Among them, we found that the target product can be obtained mostefficiently when Pd(OAc)2 and phosphine ligand with cyclohexyl groups are used as catalysts. Finally,
three types of isotope-labeled 5-ALA, 15N-labeled 5-ALA, 1-13C,15N-labeled 5-ALA, 2-13C,15N-labeled 5ALA, were synthesized using this method.
In the 1H NMR analysis of the three synthesized 5-ALAs with different labeling positions, the coupling
constant for the 2-position methylene moiety with 13C and 15N differed depending on the bond distance.

5-࢔࣑ࣀࣞࣈࣜࣥ㓟㸦5-ALA㸧ࡣࢡࣟࣟࣇ࢕ࣝࡸ࣒࣊㸪ࣇ࢕ࢥࣅࣜࣥ࡞࡝ࡢࢸࢺࣛࣆ࣮ࣟࣝ㢮⦕యࡢ๓㥑య࡜ࡋ࡚㸪඲࡚ࡢ⏕≀࡟ᬑ㐢ⓗ࡟Ꮡᅾࡍࡿ࢔࣑ࣀ㓟ࡢ୍ࡘ࡛࠶ࡿ㸬ගྜᡂࢆ⾜࠺ཎ᰾⏕≀ࢩ࢔ࣀࣂࢡࢸࣜ࢔ࡣ᳜≀ࡢⴥ⥳యࡢ㉳※࡜࡞ࡗࡓ⏕≀࡛࠶ࡿࡀ㸪୍㒊ࡢࢩ࢔ࣀࣂࢡࢸࣜ࢔ࡣ
࿘ᅖࡢගࡢⰍࢆឤ▱ࡋ࡚Ⰽ⣲ࢱࣥࣃࢡ㉁ࢆኚ໬ࡉࡏࡿ⿵Ⰽ㡰໬ࢆ♧ࡍࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿ㸬ᡃࠎࡣࡇࢀࡽࢩ࢔ࣀࣂࢡࢸࣜ࢔ࡢ⿵Ⰽ㡰໬࡟࠾࠸࡚ගࢭࣥࢱ࣮ࢱࣥࣃࢡ㉁࡜ࡋ࡚ാࡃRcaEࡢ㉥Ⰽග྾཰ᆺศᏊᵓ㐀ࢆX⥺⤖ᬗᵓ㐀ゎᯒ㸪ศᏊືຊᏛィ⟬㸪࠾ࡼࡧNMR࡟ࡼࡗ࡚ゎ᫂ࡋ㸪୰࡛ࡶ5-ALA
࠿ࡽྜᡂࡉࢀ࡚RcaEࡢග྾཰ࡢ୰ᚰ࡜࡞ࡿࣅࣜࣥⓎⰍᅋࡢࣉࣟࢺࣥ໬≧ែࡢ┤᥋ほ ࢆNMR࡟ࡼࡗ࡚ᡂຌࡋࡓ1㸬௒ᅇᡃࠎࡣ㸪⥳Ⰽග྾཰ᆺRcaEࡢࣅࣜࣥⓎⰍᅋ࿘㎶࡟࠾ࡅࡿࢱࣥࣃࢡ㉁ഃࡢ
ࣉࣟࢺࣥ໬≧ែࡸ❧యᵓ㐀ࡢNMRゎᯒࢆ⾜࠺ࡓࡵ㸪Ᏻᐃྠ఩య࡛ᶆ㆑ࡋࡓࣅࣜࣥⓎⰍᅋࢆᵓ⠏ࡍࡿࡓࡵࡢᶆ㆑໬5-ALAࡢྜᡂࢆ⾜ࡗࡓ㸬ᶆ㆑໬5-ALAࡢྜᡂNᮎࢆಖㆤࡋࡓࢢࣜࢩࣥࡢ࢝ࣝ࣎ࣥ㓟ሷ໬≀ࢆ⤒⏤ࡍࡿ᪉ἲࡀ᪤࡟ሗ࿌ࡉ
ࢀ࡚࠸ࡿ2㸬ࡋ࠿ࡋᮏἲࢆ㏣ヨࡋࡓ࡜ࡇࢁ཰⋡ࡀ༑ศ࡛ࡣ࡞ࡃ෌⌧ᛶࡶప࠸ࡇ࡜ࡀศ࠿ࡗࡓ㸬ⓎⰍᅋࡢᶆ㆑࡟ࡣ༑ศ㔞ࡢᶆ㆑໬5-ALAࡀᚲせ࡜࡞ࡿࡓࡵᮏἲ࡛ࡢྜᡂ࡟ࡣࣜࢫࢡࡀక࠺ࡓࡵ㸪᪂ࡓ࡞ྜᡂἲࡢ㛤Ⓨ࡟╔ᡭࡋࡓ㸬ࢥࢫࢺ㠃࠿ࡽᶆ㆑໬ࢢࣜࢩࣥࢆฟⓎཎᩱ࡜ࡍࡿྜᡂ⤒㊰ࡣ᪤▱ἲ࠿ࡽኚ᭦ࡏࡎ㸪Nᮎಖㆤ໬ࢢࣜࢩࣥࡢ࢝ࣝ࣎࢟ࢩᇶࢆࢳ࢚࢜ࢫࢸࣝ໬ࡋ࡚᭷ᶵள㖄ヨ⸆࡜ࡢ⚟ᒣࢡࣟࢫ࢝ࢵࣉࣜࣥࢢ཯ᛂࢆ᳨ウࡋࡓ࡜ࡇࢁ㸪ゐ፹࡜ࡋ࡚㓑㓟ࣃࣛࢪ࣒࢘࡜ࢩࢡࣟ࣊࢟ࢩࣝ࣍ࢫࣇ
࢕ࣥࡢ⤌ྜࡏࢆ⏝࠸ࡿࡇ࡜࡛㧗࠸཰⋡࡜෌⌧ᛶࢆ᭷ࡍࡿ᮲௳ࢆぢฟࡋࡓ(Fig. 1)㸬
5-࢔࣑ࣀࣞࣈࣜࣥ㓟㸪⚟ᒣ࢝ࢵࣉࣜࣥࢢ཯ᛂ㸪ྠ఩యᶆ㆑໬ྜ≀‫ࡋࢁࡦࡲࡸ࠾࠶ۑ‬㸪࠸࠸࡙࠿ࡺ࠺ࡍࡅ㸪࡞ࡀ࠼ࡓ࠿ࡺࡁ㸪ࡦࢁࡏࡺ࠺㸪ࡳࡋࡲࡲࡉࡁ

－ 294 －

Fig. 1. New method for the synthesis of 5-ALA by Pd-catalyzed Fukuyama coupling reaction.
Ⰻዲ࡞཯ᛂ᮲௳ࢆぢฟࡍࡇ࡜ࡀ࡛ࡁࡓࡓࡵ㸪ᐇ㝿࡟15Nᶆ㆑㸪15N,1-13Cᶆ㆑㸪15N,2-13Cᶆ㆑ࡢ୕✀ࡢᶆ㆑໬ࢢࣜࢩࣥࢆ⏝࠸࡚ᑐᛂࡍࡿᶆ㆑໬5-ALAࡢྜᡂࢆ⾜ࡗࡓ㸬ࡑࡢ⤖ᯝ㸪࠸ࡎࢀࡢཎᩱ࠿
ࡽࡶၥ㢟࡞ࡃ཯ᛂࡣ㐍⾜ࡋ࡚᭱⤊ⓗ࡟ࢢ࣒ࣛࢫࢣ࣮࡛ࣝ඲࡚ࡢᶆ㆑໬5-ALAࢆᚓࡿࡇ࡜࡟ᡂຌࡋ
ࡓ(Fig. 2)㸬⌧ᅾ㸪ࡇࢀࡽ໬ྜ≀ࢆ⏝࠸ࡓ⏕໬Ꮫᐇ㦂࠾ࡼࡧゎᯒࢆ⾜ࡗ࡚࠸ࡿ࡜ࡇࢁ࡛࠶ࡿ㸬
ୖ㏙ࡢ୕✀ࡢᶆ㆑໬5-ALAࡢྜᡂ୰㛫య࡟࠾ࡅࡿ1H NMRゎᯒ࡛ࡣ㸪2఩࣓ࢳࣞࣥỈ⣲࡟࠾࠸࡚ࣉࣟࢺࣥ࠿ࡽࡢ⤖ྜ㊥㞳࡟ᑐᛂࡍࡿ15N࠾ࡼࡧ13C࡜ࡢ࢝ࢵࣉࣜࣥࢢࡀほࡉࢀࡓ㸬ࡇࡢほ⤖ᯝ࠿ࡽࡶ㸪ᮃࡴ఩⨨ࢆྠ఩య࡛ᶆ㆑໬ࡋࡓ5-ALAࡢྜᡂࡀ☜ㄆ࡛ࡁࡓ㸬ᮏᡭἲ࡛ྜᡂࡋࡓ15N,1-13Cᶆ
㆑㸪15N,2-13Cᶆ㆑ࡢ5-ALAࢆ⏝࠸࡚㸪M9ᇵᆅࢆ⏝࠸࡚ࣘࢽ࣮࣒࣍15Nᶆ㆑㸪㒊ศ13Cᶆ㆑ࡢࣇ࢕ࢥࢩ
࢔ࣀࣅࣜࣥࢆ࡜ࡾࡇࢇࡔRcaEࢆㄪ〇ࡋ㸪HNCOࢱ࢖ࣉࡢᐃࢆ⾜࠺ࡇ࡜࡛㸪ࣇ࢕ࢥࢩ࢔ࣀࣅࣜࣥ

ࡢD⎔ࡢNHࡢᖐᒓ࡟ᡂຌࡋࡓࠋᮏ࣏ࢫࢱ࣮Ⓨ⾲࡛ࡣ㸪RcaE୰ࡢࣇ࢕ࢥࢩ࢔ࣀࣅࣜࣥࡢᐇ㝿ࡢNMRࢫ࣌ࢡࢺࣝࠊᖐᒓἲ࡟ࡘ࠸࡚ࡶ⤂௓ࡍࡿ㸬

Fig. 2. Structures of isotope-labeled 5-ALAs.
References(1) Nagae, T., Unno M., Koizumi, T., Miyanoiri, Y., Fujisawa, T., Masui, K., Kamo, T., Wada, K., Eki, T., Ito,
Y., Hirose, Y., and Mishima M. (2021) Structural basis of the protochromic green/red photocycle of thechromatic acclimation sensor RcaE. Proc. Natl. Acad. Sci. U.S.A. 118, e2024583118.
(2) Iida, K. and Kajiwara, M. (2002) Synthesis of 13C and 15N multilabeled 5-aminolevulinic acid. J. Label.
Compd. Radiopharm. 45, 139–143.

ㅰ㎡ᮏ◊✲ࡢ NMRᐃࡣ㸪ᩥ㒊⛉Ꮫ┬ඛ➃◊✲ᇶ┙ඹ⏝ಁ㐍஦ᴗࠕNMR ඹ⏝ࣉࣛࢵࢺࣇ࢛࣮

࣒ࠖ㸦⌮◊ᶓ὾㸧࡜⺮ⓑ◊ᣐⅬ஦ᴗ NMR ඹྠ฼⏝◊✲㸪ᮾி㒔❧኱Ꮫ ఀ⸨㝯ᩍᤵ㸪ᰴᘧ఍♫
CRYO SHIP ࡢ⚄㔝ᬛྖẶ࡟ࡈᨭ᥼࠸ࡓࡔࡁࡲࡋࡓ㸬－ 295 －

P73

MDィ⟬, ῝ᒙᏛ⩦ࢆά⏝ࡋࡓࢱࣥࣃࢡ㉁」ྜయゎᯒ‫ۑ‬ᑠᯘ┤ᏹ1, ᑠ἟๛2, ᭷⏣ᜤᖹ2, ụୖ㈗ஂ2, ᒣᓮಇኵ11⌮໬Ꮫ◊✲ᡤᶓ὾஦ᴗᡤ ⏕࿨ᶵ⬟⛉Ꮫ◊✲ࢭࣥࢱ࣮
2ᶓ὾ᕷ❧኱Ꮫ ⏕࿨་⛉Ꮫ◊✲⛉

Analysis of protein complex using MD simulation and deep learning.
‫ۑ‬Naohiro Kobayashi1, Tusyoshi Konuma2, Kyouhei Arita2, Takahisa Ikegami2, Toshio Yamazaki1
1

RIKEN Center for Biosystems Dynamics Research, Yokohama

2

Graduate School of Medical Life Science, Yokohama City University
Solution NMR analysis of protein complexes provides information on not only protein-protein interactions,but also on the dynamic states and structural changes upon complex formation as well as related to themechanistic information of their biological functions. There are many cases that cannot be solved by X-ray
crystallography or cryo-EM, especially in the case of small protein complexes with low binding affinity orwith regions of high mobility within the complex structure. On the other hand, we often encounter the similardifficulty in solution NMR to the samples having poor crystallizing tendency, such as overlapping and line
broadening or missing NMR signals. In this study, we report on a case study of two small protein complexes
in which deep learning and MD calculations are effectively utilized to expedite complex analysis.
⁐ᾮNMRࢆ⏝࠸ࡓ」ྜయゎᯒࡣࣜ࢞ࣥࢻ࡜ࡢ
┦஫స⏝࡟ࡘ࠸࡚༢࡞ࡿ❧యᵓ㐀᝟ሗࡤ࠿ࡾ࡛
ࡣ࡞ࡃ, ⤖ྜぶ࿴ᛶ(Kd), ໬Ꮫ㔞ㄽ, ືⓗᵓ㐀ኚ໬࡞࡝㇏ᐩ࡞᝟ሗࢆ୚࠼ࡿ. ࡑࡢ୍᪉࡛, 」ྜయ
ゎᯒ࡛ࡣࣜ࢞ࣥࢻ࡜ࡢ⤖ྜ࡟ࡼࡿศᏊ㔞ࡢቑ኱ࡤ࠿ࡾ࡛ࡣ࡞ࡃ, 」ྜయᙧᡂ࡟࠾ࡅࡿ㏿ᗘㄽ࡟ࡼࡿNMRಙྕࡢ⥺ᖜቑ኱࠶ࡿ࠸ࡣᾘኻ࡞࡝࡜࠸ࡗ
ࡓᅔ㞴ࢆక࠺ࢣ࣮ࢫࡣከ࠸. ࡇࢀ࡟ᑐࡋ࡚X⥺⤖ᬗゎᯒࡣศᏊ㔞ࡢୖ㝈ࡣ↓࠸ࡶࡢࡢ」ྜయ⮬యࡀ᭷ࡍࡿ⤖ᬗᛶ࡟౫Ꮡࡋ, ≉࡟࣮ࣝࣉ࠶ࡿ࠸ࡣN
ᮎ, Cᮎഃ࡟㛗࠸ࢸ࣮ࣝᵓ㐀ࢆᣢࡘ࡞࡝ᶵ⬟Ⓨ⌧࡟ᚲせ࡜࡞ࡿࡀ㐠ືᛶࡢ㧗࠸㡿ᇦࢆྵࡴሙྜࡣ
ࡑࡶࡑࡶ⤖ᬗ໬ࡋ࡞࠸, ࠶ࡿ࠸ࡣ᭷ຠ࡞㟁Ꮚᐦᗘࡀᚓࡽࢀ࡞࠸, ⤖ᬗ᫬࡟࠾ࡅࡿࣃࢵ࢟ࣥࢢຠᯝ࡞
࡝ពᅗࡋ࡞࠸⤖ᯝࢆࡶࡓࡽࡋ࡚ࡋࡲ࠺஦ࡣከ࠸.
㏆ᖺ㐍Ṍࡢ⃭ࡋ࠸ࢡࣛ࢖࢜㟁㢧ゎᯒ࡟࠾࠸࡚ࡶ
㐠ືᛶࡢ㧗࠸㡿ᇦ࡛ࡣྠᵝࡢ஦㇟࡟ᝎࡲࡉࢀࡿ

Figure 1. (A) Chimeric protein construct ofZinc-finger and peptide. (B) Overlaid ribbon
models of solution structure (gray) determined
by NMR and predicted one by AF2 (black).
The side-chains involved in binding to threezinc ions are also shown.

࡜࡜ࡶ࡟80~100kDa࡯࡝ࡢศᏊ㔞ⓗ࡞ୗ㝈ࡣᏑᅾࡍࡿ. ࡉ࡚, ࡇࡢ5ᖺ࠶ࡲࡾࡢ㛫࡟ᛴ㏿࡟Ⓨᒎࡋ࡚࠸ࡿ῝ᒙᏛ⩦ࡣGPUGPU࡟ࡼࡿ㉸୪ิィ⟬ࡢ㧗㏿໬࡟ຓࡅࡽࢀᵝࠎ࡞ศ㔝࡛ࡲࡉ࡟”ேᕤ▱⬟”࡜ゝ࠼ࡿࣞ࣋ࣝࡢ≀యㄆ㆑ࡸᶵᲔ⩻ヂ࡞࡝࡟࠾࠸࡚㧗࠸ᛶ⬟ࢆⓎ᥹ࡋ, ከࡃࡢ◊✲ศ㔝࡛ࡶศᏊືຊᏛ㸪῝ᒙᏛ⩦, 」ྜయ
‫ࢁࡦ࠾࡞ࡋࡸࡤࡇۑ‬, ࡇࡠࡲࡘࡼࡋ,࠶ࡾࡓࡁࡻ࠺࡬࠸, ࠸ࡅࡀࡳࡓ࠿ࡦࡉ, ࡸࡲࡊࡁ࡜ࡋ࠾

－ 296 －

ᡂᯝࢆ୚࠼࡚࠸ࡿ. Google DeepMind ࡟ࡼࡗ࡚㛤Ⓨࡉࢀ, ᫖ᖺබ㛤ࡉࢀࡓAlphaFold2 (AF2) ࡣ㓄ิ࠿ࡽ┤᥋ⓗ࡟❧యᵓ㐀ࢆணࡍࡿࢥࣥࢸࢫࢺ࡛࠶ࡿCASP14࡟࠾࠸࡚ᅽಽⓗ࡞ᛶ⬟ࢆ♧ࡋࡓ(1).

᭦࡟ࡣAF2ࢆ฼⏝ࡋࡓ」ྜయᵓ㐀ண ࡲ࡛ࡶᡂຌ౛ࡀ♧ࡉࢀ(2), AF2ࢆά⏝ࡋࡓᵓ㐀⏕≀Ꮫ◊✲ࡣ௒ᚋࡲࡍࡲࡍᗈࡀࡗ࡚࠸ࡃࡶࡢ࡜ᛮࢃࢀࡿ.
ᮏ◊✲࡛ࡣ㞴᫆ᗘࡢ㧗࠸」ྜయゎᯒࢆ῝ᒙᏛ⩦ᢏ⾡ࡸMDィ⟬ࢆά⏝ࡋ࡚ゎỴࡋࡓ1ࡘ┠ࡢࢣ࣮ࢫ࡜ࡋ࡚, ᶓ὾ᕷ❧኱᭷⏣ࡽࡣzinc-fingerࢱࣥࣃࢡ㉁࡜IDP࣌ࣉࢳࢻࢆ⼥ྜࡉࡏࡓ࣓࢟ࣛᵓ㐀యࢆసᡂ࡟ᡂຌࡋ, 㧗⢭ᗘ࡞NMRᵓ㐀ࢆᚓࡓ. ᭦࡟AF2࡟ࡼࡿ㓄ิ࠿ࡽணࡉࢀࡓ❧యᵓ㐀ࡣNMRᵓ㐀࡜୺㙐RMSDࡣ཰᮰㡿ᇦ࡛~0.9Å࡜ࡼࡃ୍⮴ࡋࡓ(Fig. 1). ࡲࡓ, ᚓࡽࢀࡓ」ྜయᵓ㐀࠿ࡽᶵ⬟ࢆ㜼ᐖࡍࡿ࡜ண᝿ࡉࢀࡿṧᇶࢆኚ␗ࡉࡏࡓᵓ㐀ࡶAF2࡟ࡼࡾணࡋ, ⏕໬Ꮫᐇ㦂࡜ࡢᩚྜᛶࡀᚓࡿ

ࡇ࡜࡟ᡂຌࡋࡓ(3).
2 ࡘ┠ࡢ ࢣ࣮ࢫ ࡜ࡋ࡚ ᶓ὾ ᕷ❧኱ ᑠ἟ࡽࡣ ᑠࡉ࡞ Ș -helix ࢱ ࣥࣃࢡ㉁࡛ ࠶ࡿ ET-domain࡜
COVID-19ࡢឤᰁ࡟㛵ࢃࡿ18ṧᇶࡢ▷࠸࣌ࣉࢳࢻ(P18)࡜ࡢ┦஫స⏝ゎᯒ࡟ࡘ࠸࡚♧ࡍࡇ࡜ࢆぢฟࡋࡓ. ET-domain࡜P18࡜ࡢKdࡣ100~200mM࡜ᴟࡵ࡚ᙅ࠸ࡓࡵ, ET-domain:P18 ࣓࢟ࣛ⼥ྜయࡢసᡂ ࡣ ᡂ ຌ ࡋ ࡞ ࠿ ࡗ ࡓ . ୍ ᪉ ࡛ Kd ࡢ ᙅ ࡉ ࠿ ࡽ fast-exchange ࡟ ࡼ ࡿ HSQC ⁲ ᐃ ᐇ 㦂 ࢆ ⾜ ࠸ , ETdomain:P18 ࡢKd࡜」ྜయᙧᡂ᫬࡟࠾ࡅࡿ໬ᏛࢩࣇࢺࢆỴᐃࡍࡿࡇ࡜࡟ᡂຌࡋࡓ. 㧗⃰ᗘࡢP18Ꮡ
ᅾୗ, ẚ㍑ⓗప

(283K) ࡛ ࡢ NMR

ᐃ ࡟ ࡼ ࡾ NMR ಙ ྕ ࡣ ᴟ ࡵ ࡚ ࣈ ࣟ ࣮ ࢻ ࡛ ࠶ ࡿ ࡀ

MagRO_NMRViewJ ࢆ ⏝ ࠸ ࡓ ゎ ᯒ ࡟ ࡼ ࡾ ETdmain:P18」ྜయࡢศᏊෆ࠾ࡼࡧศᏊ㛫NOEࢆỴᐃࡍࡿࡇ࡜ࡀ࡛ࡁࡓ. ࡲࡓศᏊ㛫NOEࡣ㔜࡞ࡾྜ࠸ࡀ⃭ࡋ࠸ࡓࡵCYANAィ⟬࡛ࡣ᭕᫕࡞㊥㞳ไ㝈ࢆ⦆ࡃ㐺⏝ࡍࡿࡇ࡜࡛」ྜయࣔࢹࣝࢆᚓࡓ. ⯆࿡῝࠸஦࡟௬᝿ⓗ࡞࣓࢟ࣛ⼥ྜయࡣAF2࡟ࡼࡾ」ྜయᵓ㐀ணࢆᐇ⾜ࡋ, P18ࡀ⤖ྜࡍࡿ࣮ࣔࢻ࡜ࡋ

࡚཯ᖹ⾜࠶ࡿ࠸ࡣᖹ⾜ࢩ࣮ࢺ㸰ࡘࡢࣔࢹࣝࡀ 6:4
ࡢẚ࡛ᚓࡽࢀࡓ. ᖹ⾜ࣔࢹ࡛ࣝࡣP18-Phe࡟ࡼࡗ࡚㧗☢ሙࢩࣇࢺࡍࡿET-domian Ile࣓ࢳࣝᇶࡢ໬Ꮫ
ࢩࣇࢺࢆㄝ᫂ࡍࡿࡇ࡜ࡀ࡛ࡁ࡞࠸. ࡲࡓⓎ⾲⪅࡟ࡼࡗ࡚㛤Ⓨࡉࢀࡓᵓ㐀࠿ࡽ໬Ꮫࢩࣇࢺ᥎ᐃࡍࡿ
ࢶ࣮ࣝ࡟ࡼࡾ(4) , ཯ᖹ⾜ࣔࢹࣝࡀṇࡋ࠸஦ࢆ♧ࡋࡓ. ᭦࡟Amber20 PEMD (Perticle Mesh Ewald)
࡟ࡼࡿexplicit water MDィ⟬ࢆ⾜࠸, ཯ᖹ⾜ࢩ࣮ࢺࣔࢹࣝᵓ㐀࡟࠾ࡅࡿP18-Phe࡜ET-dominain Ileࡀ┦஫స⏝ࡋ࡚࠸ࡿ≧ែࡣ࢚ࢿࣝࢠ࣮ⓗ࡟Ᏻᐃ

Figure 2. Ribbon models of ET-domain andP19 complex.
Anti-parallel (upper left) and parallel (upper
right) sheet models predicted by AF2. The
ribbon models determined by solution NMR are
also shown (bottom).

࡛࠶ࡿࡇ࡜ࢆ♧ࡋࡓ.
References(1) Jumper, J. et al., (2021) Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589.
(2) Bryant, P. et al., (2022) Improved prediction of protein-protein interactions using AlphaFold2. Nat. Comm.
13, 1265-1276.
(3) Hata. K. et al., Structural basis for the unique multifaceted interaction of DPPA3 with the UHRF1 PHD
finger. BioRxiv.
(4) Kobayashi, N. et al., ISMAR 2021, Japan.

－ 297 －P74Y

GMPPNP⤖ྜᆺK-Ras4BG12V࡜Rgl2RBDࡢ┦஫స⏝ゎᯒ‫ۑ‬ᐩᶔ┤அ{㸪ᐑ⏣⿱㈗{㸪ட஭ 㥴{㸪Ⳣ⃝ࡣࡿ࠿{㸪⨾ᕝ ົu㸪⊦⫤᫭௓{㸪⏣௰ຍ௦Ꮚt㸪ఀ⸨ 㝯{㸪ụ㇂㕲ර{1ᮾி㒔❧኱Ꮫ࣭኱Ꮫ㝔⌮Ꮫ◊✲⛉2ࣞࢫࢱ࣮኱Ꮫ࣭ศᏊ⣽⬊⏕≀Ꮫ⛉
3⌮໬Ꮫ◊✲ᡤ࣭⏕࿨ᶵ⬟⛉Ꮫࢭࣥࢱ࣮

Structural analysis by solution NMR reveals a unique interaction between GMPPNP-boundK-Ras4BG12V and Rgl2RBD‫ۑ‬Naoyuki Togashi1, Hiroki Miyata1, Shun Kamei1, Haruka Sugasawa1, Tsutomu Mikawa3, Kohsuke
Inomata1, Kayoko Tanaka2, Yutaka Ito1, and Teppei Ikeya1
1
Department of Chemistry, Tokyo Metropolitan University, Japan
2Department of Molecular and Cell Biology, University of Leicester, UK
RIKEN, Quantitative Biology Center, Japan
K-Ras4BG12V, a proto-oncogene product, plays a role in transmitting important signals related to cellproliferation and differentiation downstream through interaction with various effector proteins such as Raf,
PI3K and RalGDS. Recently, it has been reported that the Rgl1/Rgl2-RalB pathway is particularly crucial for
RAS-dependent invasiveness of transformed cells1, and NMR-based competition experiments between
several effector proteins and K-Ras have shown a high affinity of Rgl1 upon K-Ras2. In this study, we
performed the protein structure determination of the RAS-binding domain (RBD) of Rgl2 and titration
experiments with 15N-labelled samples to analyze the interaction between K-Ras4BG12V and Rgl2RBD. These
results demonstrated that the conformations and dynamics at the interface between Rgl2RBD and K-Ras4BG12V
change when their interaction occurs, suggesting that this recognition mechanism is partially different fromthat of K-Ras4BG12V and RalGDS.
࠙ᗎㄽࠚཎࡀࢇ㑇ఏᏊ⏘≀࡛࠶ࡿK-Rasࡣ࢔࣑ࣀab
㓟189ṧᇶ࠿ࡽ࡞ࡿ21kDaࡢపศᏊ㔞GTPase࡛࠶ࡾ㸪GTP࠾ࡼࡧGDP࡜ᙉࡃ⤖ྜࡍࡿ㸬ࡇࡢ࠺ࡕ
GTP⤖ྜᆺࡢK-RasࡣRafࡸPI3K㸪Ral࡜࠸ࡗࡓᵝࠎ࡞࢚ࣇ࢙ࢡࢱ࣮⺮ⓑ㉁࡜ࡢ┦஫స⏝ࢆ௓ࡋ
Fig. 1. Superposition of the structures of࡚㸪⣽⬊ቑṪ㸪㐟㉮㸪᥋╔㸪ศ໬㸪ᾐ₶࡟㛵ࢃࡿ
Rgl2RBD. (a) Superposition of 20 NMR structures㔜せ࡞⣽⬊ෆࢩࢢࢼࣝఏ㐩⤒㊰ࢆάᛶ໬ࡍࡿ㸬㏆
of Rgl2RBD (light grey). (b) Superposition of the coᖺ㸪Ras౫Ꮡᛶ࡞ᙧ㉁㌿᥮⣽⬊ࡢᾐ₶ᛶ࡟ࡘ࠸࡚
crystal structure of Rgl2RBD with K-Ras4BG12V
ࡣ㸪Rgl1/2-RalB⤒㊰ࡀ≉࡟㔜せ࡛࠶ࡿࡇ࡜ࡀሗ࿌
(grey) and NMR structure of the monomericࡉࢀ࡚࠾ࡾ[1]㸪NMRࢆ⏝࠸ࡓ」ᩘࡢ࢚ࣇ࢙ࢡ
Rgl2RBD (light grey).
ࢱ࣮⺮ⓑ㉁࡜K-Rasࡢ➇ྜᐇ㦂࠿ࡽࡣ㸪Rgl1ࡀ௚
ࡢ࢚ࣇ࢙ࢡࢱ࣮⺮ⓑ㉁࡜ẚ࡭K-Ras࡜㧗࠸⤖ྜぶ࿴ᛶࢆ᭷ࡍࡿࡇ࡜ࡀ♧ࡉࢀ࡚࠸ࡿ[2]㸬
ᮏ◊✲࡛ࡣ㸪ෆᅾᛶGTPaseάᛶࡀⴭࡋࡃపୗࡋ࡚࠸ࡿⓎࡀࢇᛶࡢኚ␗య࡛࠶ࡿK-Ras4BG12V࡜
Rgl1/2ࡢศᏊㄆ㆑ᶵᵓࢆゎ᫂ࡍࡿࡓࡵ࡟㸪Rgl2ࡢRas-binding domain㸦RBD㸧ࡢ❧యᵓ㐀Ỵᐃ࡜㸪
K-Ras㸪❧యᵓ㐀Ỵᐃ㸪⺮ⓑ㉁㛫┦஫స⏝ゎᯒ‫ࡁࡺ࠾࡞ࡋࡀ࡜ۑ‬㸪ࡳࡸࡓࡦࢁࡁ㸪࠿ࡵ࠸ࡋࡹࢇ㸪ࡍࡀࡉࢃࡣࡿ࠿㸪ࡳ࠿ࢃࡘ࡜ࡴ㸪࠸ࡢࡲࡓࡇ
࠺ࡍࡅ㸪࠸࡜࠺ࡺࡓ࠿㸪ࡓ࡞࠿࠿ࡼࡇ㸪࠸ࡅࡸ࡚ࡗ࡮࠸

－ 298 －

K-Ras4BG12V࡜Rgl2RBDࡢ┦஫స⏝ゎᯒࢆ⾜ࡗࡓ㸬a࠙ᐇ㦂ࠚRgl2RBD࡟ࡘ࠸࡚ࡣ㸪୺㙐࠾ࡼࡧഃ㙐NMRࢩࢢࢼࣝࡢᖐᒓ࡜㸪NOE⏤᮶ࡢ㊥㞳ไ㝈ࢆ⏝࠸ࡓ❧యᵓ㐀ィ⟬ࢆ⾜࠸㸪ヲ⣽࡞⁐ᾮᵓ㐀ࢆỴᐃࡋ
ࡓ㸬K-Ras4BG12V࡟ࡘ࠸࡚ࡣ㸪Cᮍ➃20࢔࣑ࣀ㓟ṧᇶࢆ㝖ཤࡋࡓヨᩱ㹙K-Ras4BG12V(1-169)㹛ࢆㄪ〇ࡋ㸪
GTPࡢ㠀Ỉゎ࢔ࢼࣟࢢ࡛࠶ࡿGMPPNPࢆ⤖ྜࡉࡏࡓᚋ㸪୺㙐࠾ࡼࡧഃ㙐NMRࢩࢢࢼࣝࡢᖐᒓࢆ⾜ ࡗ ࡓ 㸬 ḟ ࠸ ࡛ 㸪 15N ᶆ ㆑ య ࡜ 㠀 ᶆ ㆑ య ࡢ KRas4BG12V ࡜Rgl2RBD ࢆࡑࢀࡒࢀ⏝ពࡋ࡚NMR⁲ᐃᐇ㦂ࢆ⾜࠸㸪⺮ⓑ㉁㛫┦஫స⏝ゎᯒࢆ⾜ࡗࡓ㸬brelative intensity࠙⤖ᯝ࡜⪃ᐹࠚ⁐ᾮNMR࡜X⥺⤖ᬗᵓ㐀ゎᯒ࡟ࡼࡿᵓ㐀ゎᯒ࠿ࡽ㸪Rgl2RBDࡣ㸪༢య࡜K-Ras4BG12V࡜
ࡢ」 ྜయ࡛ࡼࡃ 㢮ఝࡋࡓᵓ 㐀࡛࠶ࡿࡇ ࡜ࡀࢃ
࠿ࡗࡓ (Fig .1)㸬୍᪉࡛㸪┦஫స⏝㠃࡜᥎ᐃࡉࢀࡿ
residue number㡿ᇦࡢ୍㒊࡛㸪༢య࡛ᵓ㐀ࡢ཰᮰ᗘࡀప࠸㒊ศࡀ Fig. 2. NMR titration experiment of 15N࠶ࡾ㸪ࡲࡓྠ᫬࡟ࡇࡢ㒊ศࡣ」ྜయ୰࡜ࡣࡸࡸ␗ Rgl2RBD with the unlabeled K-Ras4BG12V࡞ࡿ ❧యᵓ㐀ࢆ ♧ࡋ࡚࠸ࡓ 㸬ࡇࡢࡇ࡜ ࠿ࡽ㸪 GMPPNP. (a) Overlays of 2D 1H-15N-HSQC
RBD
with
Rgl2RBDࡣ㸪」ྜయᙧᡂ᫬࡟⤖ྜ㠃ࡢᵓ㐀࡜ࢲ࢖ࢼ spectra from multipoint titrations of Rgl2
G12V
K-Ras4B-GMPPNP.
The
color
codes
showing࣑ࢡࢫࢆኚ໬ࡉࡏ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓ㸬the molar ratio of Rgl2RBD:K-Ras4BG12VFig.2࡟ࡣ㸪K-Ras4BG12Vࡢῧຍ࡟ࡼࡿRgl2RBDࡢGMPPNP are as follows: light gray (1:0), gray
1H-15N HSQC ࢫ ࣌ ࢡ ࢺ ࣝ ኚ ໬ ࢆ ♧ ࡋ ࡓ 㸬 K(1:1), black (1:3). Representative peaks showing
Ras4BG12Vࡢῧຍ࡟కࡗ࡚ࢩࢢࢼࣝᙉᗘࡢపୗ࡜㸪 large chemical shift perturbations and intensity᪂ࡓ࡞ࣆ࣮ࢡࡢฟ⌧㸪࠾ࡼࡧ໬Ꮫࢩࣇࢺኚ໬ࡀྠ changes are indicated by arrows. (b) Intensity᫬࡟ほ ࡉࢀࡓ㸬ࡇࢀࡽࡢ⤖ᯝ࠿ࡽ㸪K-Ras4BG12V ratios derived from the titration experiment.
࡜Rgl2RBDࡢ┦஫స⏝ࡀ㸪」ᩘࡢ⤖ྜ࣮ࣔࢻ࠿ࡽ࡞
ࡿࡇ࡜ࡀண᝿ࡉࢀࡓ㸬Fig.3࡟ࡣ㸪ࢩࢢࢼࣝᙉᗘప
ୗࡢኚ໬㔞ࢆRgl2RBD❧యᵓ㐀ୖ࡟࣐ࢵࣆࣥࢢࡋ
ࡓᅗࢆ♧ࡍ㸬ゎᯒࡢ⤖ᯝ㸪Rgl2RBDࡢࣆ࣮ࢡᙉᗘኚ
໬ࡣ㸪K-Ras4BG12V࡜RalGDSࡢ」ྜయ࠿ࡽண᝿ࡉ
15
RBDࢀࡿ┦஫స⏝㠃࡜㢮ఝࡋࡓ㡿ᇦ࡛ぢࡽࢀࡓ㸬୍᪉ Fig. 3. Peak intensity decay for N-Rgl2 .
࡛㸪┦஫స⏝㒊఩࠿ࡽ㞳ࢀࡓ㡿ᇦ࡟࠾࠸࡚ࡶኚ໬ Residues are color-coded by relative peakintensity, as indicated in the color bar, on theࡀ ほ ࡉ ࢀ ࡓ 㸬 ⏣ ௰ ࡽ ࡟ ࡼ ࡿ K-Ras4BG12V 㸫
ribbon model of the monomeric Rgl2RBD.
Rgl2RBD」ྜయࡢ⤖ᬗᵓ㐀ࡢ⤖ᯝ[3]࡜ྜࢃࡏ࡚⪃ᐹࡍࡿ࡜㸪K-Ras4BG12V-Rgl2RBDࡢ┦஫స⏝ᵝᘧࡣ㸪RalGDSࡢࡶࡢ࡜୍㒊␗࡞ࡗ࡚࠸ࡿྍ⬟ᛶࡀ♧၀ࡉࢀࡓ㸬⌧ᅾ㸪⁐ᾮ୰࡛ࡢ」ྜయᙧᡂ࡟࠾ࡅࡿ⤖ྜ࣮ࣔࢻࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵ࡟㸪2H/13C/15N-KRas4BG12V-Rgl2RBD」ྜయࢆ⏝࠸ࡓK-Ras4BG12Vࡢ⤖ྜ㠃ࡢゎᯒ࡟ྲྀࡾ⤌ࢇ࡛࠸ࡿ㸬࠙ཧ⪃ᩥ⊩ࠚ[1] Zago, G. et al. Ralb directly triggers invasion downstreanm ras by mobilizing
the wave complex. Elife 7, 1-23 (2018).[2] Smith, M. J. & Ikura, M. Integrated RAS signaling definedby parallel NMR detection of effectors and regulators. Nat. Chem. Biol. 10, 223-230 (2014)., [3] Mishal, T.
Teppei, I. Naoyuki, T. et al. K-Ras4B and Rgl2 complex highlights a distinct RAS:effector binding mode for
guanine nucleotide exchange factors of RalA/B. in preparation.

－ 299 －

P75

NMRࢆ⏝࠸ࡓࢩࣕࣝࢥ࣮࣭࣐࣮࣭ࣜࢺ࣮ࢗࢫ⑓ࡢཎᅉ㑇ఏᏊ⏘≀࣑࢚ࣜࣥࢱࣥࣃࢡ㉁ࢮࣟ㸦MPZ㸧ࡢᵓ㐀ゎᯒ‫ۑ‬ᆏ಴ṇ⩏㸪୕ᑿ࿴ᘯ2㸪⏣㎶ᖿ㞝31ᶓ὾ᕷ❧኱Ꮫ࣭኱Ꮫ㝔⏕࿨་⛉Ꮫ◊✲⛉⏘⥲◊࣭ᮾ኱࣭࢜࣌ࣛࣥࢻィ OIL㧗࢚ࢿᶵᵓ࣭≀ᵓ◊࣭ᵓ㐀⏕≀Structural analyses of a Charcot-Marie-Tooth disease-causative gene product, myelin
protein zero, using NMR‫ۑ‬Masayoshi Sakakura1, Kazuhiro Mio2, Mikio Tanabe3
1Graduate School of Medical Life Science, Yokohama City University
2

AIST-UTokyo operando OIL

3KEK, IMSS, SBRC

Myelin protein zero (MPZ or P0) is expressed in the peripheral myelin, and functions to adhere two
opposing membranes via homophilic interactions between the extracellular domains (ECDs) of the protein.
Single amino acid substitutions in ECD impair proper myelin formation, leading to a demyelinatingneuropathy, Charcot-Marie-Tooth disease (CMT). However, the mechanisms by which such substitutions
induce the disease have not been well understood. In this study, we analyzed the inter-ECD interaction
using NMR and found that ECDs interact via the molecular surface including W72, D80, and V84, which
was different from those observed in the crystal structure. The fact that W72, D80, and V84 are CMTrelated substitutions sites suggests this inter-ECD interaction is related to proper myelin formation and CMT.
࣑࢚ࣜࣥࢱࣥࣃࢡ㉁ࢮࣟ㸦MPZࡲࡓࡣP0㸧ࡣࠊᮎᲈ⚄⤒࣑࢚ࣜࣥࢆᵓᡂࡍࡿࢩࣗ࣡ࣥ⣽⬊ࡢ⣽⬊⭷ୖ࡟Ⓨ⌧ࡍࡿ㸯ᆺ⭷
ࢱࣥࣃࢡ㉁࡛࠶ࡾࠊ࣑࢚
ࣜࣥࡢᮏయ࡛࠶ࡿ⬡㉁஧
㔜⭷ከ㔜ᒙࡢᙧᡂ࣭⥔ᣢ࡟࠾࠸࡚୺せ࡞ᙺ๭ࢆᯝ
ࡓࡍ㸦Fig. 1A-C㸧ࠋ㑇ఏᏊኚ␗࡟క࠺MPZୖࡢ࢔࣑ࣀ㓟ṧᇶ⨨᥮ࡣࠊ࣑࢚
ࣜࣥ࡟࠾ࡅࡿ⬡㉁஧㔜⭷ከ㔜ᒙࡢᙧᡂ୙඲ࠊ࠾ࡼ
ࡧ㑇ఏᛶᮎᲈ⚄⤒⑌ᝈ࡛࠶ࡿࢩࣕࣝࢥ࣮࣭࣐ࣜ

Fig. 1. Multi-layered membranes stacked by MPZ in the PNS࣮࣭ࢺ࣮ࢗࢫ⑓㸦CMT㸧

myelin. Schematic drawings of a (A) peripheral neuron, (B) myelin,ࢆㄏ㉳ࡍࡿࡀࠊࡑࡢ࣓࢝(C) membranes stacked by MPZ molecules, and (D) the crystal structureࢽࢬ࣒࡟ࡣᮍゎ᫂ࡢⅬࡀ

of octameric human MPZ-ECD.

ከࡃṧࡉࢀ࡚࠸ࡿࠋࡇࢀ
⚄⤒⑌ᝈ㸪┦஫స⏝ゎᯒ㸪஺ᕪ㣬࿴ἲ㸪࣑࢚ࣜࣥࣉࣟࢸ࢖ࣥࢮࣟ
‫ࡋࡼࡉࡲࡽࡃ࠿ࡉۑ‬㸪ࡳ࠾࠿ࡎࡦࢁ㸪ࡓ࡞࡭ࡳࡁ࠾

－ 300 －

ࡲ࡛࡟ᡃࠎࡣࠊX ⥺⤖ᬗᵓ㐀ゎᯒ࡟ࡼࡾ MPZ ࡢ⣽⬊እࢻ࣓࢖ࣥ㸦ECD㸧ࡢከ㔞యᵓ㐀ࢆỴᐃࡋࠊ⤖ᬗ୰࡟࠾࠸࡚
ECD ࡀ㸱ࡘࡢ␗࡞ࡿࢱ࢖ࣉ
ࡢ࣍ࣔ┦஫స⏝ࢆᙧᡂࡍࡿ
ࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓࠋࡲࡓࠊ
ECD ࡢ⭷᥋╔άᛶΝ‫ݗ‬ड़ͤ
Ζ৿͢͏մੵᡭἲ㸦ࢼࣀ࣑࢚ࣜࣥἲ㸧ࢆ㛤Ⓨࡋࠊ݃ধ஦Ͷ͕͏ͱ؏଎͠Ηͪ̑ͯ͹૮‫༽ࡠޕ‬͹͑ͬɼ̐ͯ͹┦஫స⏝࡟ࡼࡾ㐃⤖ࡉࢀࡓ 8 㔞య͗ຜં஥ͶචགྷͲ͍Ζ͞ͳ
ࢆ໎Δ͖Ͷͪ͢ʤFig. 1C-Dʥࠋ୍᪉ࠊ⤖ᬗᵓ㐀࡛ほ ࡉࢀࡓ࣍ࣔ┦஫స⏝⏺㠃͖Δ֐Ηͪ෾ࢢන໚Ͷ΍ɼCMT ㄏ㉳ᆺ࢔࣑ࣀ㓟ṧᇶ⨨᥮෨Ғ͗

Fig. 2. Inter-ECD interface determined by solution NMR

ଚࡑͤΖɽࡇࢀࡽࡢ෨ҒͶ͕(A) Superimposed 1H-15N HSQC spectra of [2H, 15N]-labeled ECD with

͜Ζ࢔࣑ࣀ㓟ṧᇶ஖‫ࠊࡶ׷‬(dashed line) and without (solid line) the irradiation of non-labeledఱࡽ࠿ࡢ ECD 㛫┦஫స⏝࡟

ECD. 1D slices of the spectra for representative residues are shown atᙳ㡪ࢆ୚࠼ࠊCMT ࡟㛵୚ࡍ

right.

ࡿྍ⬟ᛶࡀ⪃࠼ࡽࢀࡿࠋࡑࡇ

structure of the 8-meric ECDs.

࡛ᮏ◊✲࡟࠾࠸࡚ࡣࠊ⤖ᬗ୰

reduced more than 30% are shown in black. Some protomers in the 8-࡛ࡣᙧᡂࡉࢀ࡞࠸ ECD 㛫┦

meric structure are omitted for clarity. The CMT-related amino acid஫స⏝ࡢ᳨ฟࢆ┠ⓗ࡜ࡋ࡚ࠊsubstitution sites are boxed.

(B) The NMR-detected interface is mapped on the crystal
Residues of which signals were

NMR ࢆ⏝࠸ࡓ⁐ᾮ୰࡟࠾ࡅ
ࡿ ECD 㛫┦஫స⏝ゎᯒࢆ⾜ࡗࡓࠋ
2H࠾ࡼࡧ15Nᶆ㆑ࢆᑟධࡋࡓECDࢆㄪ〇ࡋࠊ㠀ᶆ㆑ECD࡜1:3ࡢࣔࣝẚ࡛ΰྜࡋࡓࠋࡇࡢࢧࣥࣉ

ࣝࢆ⏝࠸࡚஺ᕪ㣬࿴ἲ࡟ࡼࡾࠊ㠀ᶆ㆑ECD࠿ࡽᶆ㆑ECD࡬ࡢศᏊ㛫☢໬⛣ືࢆほ ࡋࡓࠋࡇࡢ⤖ᯝࠊQ71ࠊW72ࠊR77ࠊW78ࠊD80ࠊV84ࢆྵࡴ㐃⥆ࡋࡓศᏊ⾲㠃ṧᇶ࡟࠾࠸࡚ศᏊ㛫☢໬⛣ື࡟
⏤᮶ࡍࡿNMRࢩࢢࢼࣝࡢῶᑡࡀほ ࡉࢀࠊࡇࢀࡽࡢṧᇶࡀECD㛫┦஫స⏝⏺㠃ࢆᙧᡂࡋ࡚࠸ࡿ
ࡇ࡜ࡀ♧ࡉࢀࡓ㸦Fig. 2㸧ࠋ୍᪉ࠊ15Nᶆ㆑ࢆ⾜ࡗࡓECD࡟ࡘ࠸࡚ࠊNMRࢩࢢࢼࣝࡢECD⃰ᗘ౫Ꮡᛶࢆゎᯒࡋࡓ⤖ᯝࠊ஺ᕪ㣬࿴ᐇ㦂࡟ࡼࡾ᳨ฟࡉࢀࡓ┦஫స⏝ᙧᡂṧᇶࢆྵࡴศᏊ⾲㠃ṧᇶ࡟࠾࠸
࡚ࠊECD⃰ᗘ౫Ꮡⓗ࡞໬Ꮫࢩࣇࢺኚ໬ࡀ᳨ฟࡉࢀࡓࠋࡲࡓࠊࡇࡢ⃰ᗘ౫Ꮡⓗ໬Ꮫࢩࣇࢺኚ໬ࡣࠊ
┦஫స⏝㒊఩ୖ࡟ᏑᅾࡍࡿW78ࢆAla࡟ኚ␗ࡉࡏࡓࣂࣜ࢔ࣥࢺ࡛ࡣほ ࡉࢀ࡞࠿ࡗࡓࠋ௨ୖࡢ
NMRᐇ㦂᳨࡛ฟࡉࢀࡓW78ࢆ୰ᚰ࡜ࡋࡓ࣍ࣔ┦஫స⏝㡿ᇦ㸦௨ୗS┦஫స⏝㡿ᇦ࡜グ㏙ࡍࡿ㸧ࡣࠊECDከ㔞యࡢ⤖ᬗᵓ㐀࡟࠾࠸࡚ࡣศᏊ㛫ࢥࣥࢱࢡࢺࢆᙧᡂࡋ࡚࠾ࡽࡎࠊ⁐ᾮ୰࡟࠾࠸࡚ࡢࡳ
ࡉࢀࡿ‽Ᏻᐃ࡞┦஫స⏝㒊఩࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿ㸦Fig. 2B㸧ࠋほS┦஫స⏝㡿ᇦ࡟ྵࡲࢀࡿW72ࠊD80ࠊV84ࡣCMT㛵㐃࢔࣑ࣀ㓟ṧᇶ⨨᥮㒊఩࡛࠶ࡿࡇ࡜࠿ࡽࠊ
ࡇࢀࡽࡢ㒊఩࡟࠾ࡅࡿ࢔࣑ࣀ㓟⨨᥮࡟క࠺S┦஫స⏝ࡢኚㄪࡀࠊ࣑࢚ࣜࣥ࡟࠾ࡅࡿ⬡㉁஧㔜⭷ከ㔜ᒙࡢᙧᡂ࡟ᙳ㡪ࢆ୚࠼ࡿྍ⬟ᛶࡀ⪃࠼ࡽࢀࡿࠋ

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P76Y

Ⅳ⣲ᮦᩱࡢ⾲㠃ᐁ⬟ᇶゎᯒ࡟࠾ࡅࡿDNP-NMRࡢ฼⏝‫ۑ‬Ᏻᮾᫎ㤶㸪㕥ᮌඞ᫂2㸪Ლᘯ඾2㸪ோ⛉ຬኴ1㸪⚄ᡞ㧗ᚿ1㸪ᚋ⸨࿴㤿11ᒸᒣ኱Ꮫ࣭኱Ꮫ㝔⮬↛⛉Ꮫ◊✲⛉2ி㒔኱Ꮫ࣭໬Ꮫ◊✲ᡤThe use of DNP-NMR for analysis of surface functional groups on carbonaceous materials‫ۑ‬Hideka Ando1, Katsuaki Suzuki2, Hironori Kaji2, Yuta Nishina1, Takashi Kambe1, Kazuma Gotoh1
1

Graduate School of Natural Science and Technology, Okayama University

2

Institute for Chemical Research, Kyoto University
Analysis of surface functional groups on carbonaceous materials is important because the functionalgroups affect properties of the carbon materials. Dynamic nuclear polarizing nuclear magnetic resonance(DNP-NMR) is expected as a powerful tool for analysis of the surface functional groups on carbon materials.
However, it has not been considered and applied to the analysis due to the electroconductivity and themicrowave absorbance of the carbon, which attenuates the enhancing effect of DNP. In this study, weinvestigated an availability of DNP-NMR for the analysis of surface functional groups on carbonaceous
materials. As results for 1H-13C CPMAS DNP-NMR measuring of graphene oxide (GO) and sucrose-derived
carbon, trace amounts of functional groups, which are difficult to measure by conventional NMR, wereobserved. The enhancement of the signals is related by not only external radicals derived from AMUPol(polarizing agent) but also internal radicals derived from samples.
ᴾ࠙ᗎㄽࠚ㓟໬ࢢࣛࣇ࢙ࣥ(GO)ࡸࣂ࢖࣐࢜ࢫᮦᩱ⏤᮶Ⅳ⣲࡞࡝ࡢ⾲㠃ᐁ⬟ᇶࢆᣢࡘⅣ⣲ᮦᩱࡣᐁ⬟ᇶࡢ✀㢮ࡸ㔞࡟ࡼࡾ␗࡞ࡿ≀ᛶࢆ♧ࡍࠋ⾲㠃ᐁ⬟ᇶࢆᣢࡘⅣ⣲ᮦᩱࡢᛂ⏝࡟ࡣ⾲㠃ᐁ⬟ᇶࡢṇ☜࡞ゎᯒࡀᚲせ୙ྍḞ࡛࠶ࡿࠋ⌧ᅾࠊⅣ⣲⾲㠃ᐁ⬟ᇶࡢゎᯒἲ࡜ࡋ࡚X⥺ග㟁Ꮚศගἲ(XPS)ࡸ᪼ ⬺㞳ἲ(TPD)➼ࡀ୺࡟⏝࠸ࡽࢀ࡚࠸ࡿࠋࡋ࠿ࡋࡇࢀࡽࡢศᯒἲ࡛ࡣྛᐁ⬟ᇶࣆ࣮ࢡࡀ㔜࡞ࡿࡓࡵྛᐁ⬟ᇶࣆ࣮ࢡࡢṇ☜࡞ゎᯒ࡟ࡣከࡃࡢ▱㆑࡜⤒㦂ࡀᚲせ࡜࡞ࡿࠋᅛయ᰾☢Ẽඹ㬆ἲ(NMR)࡛ࡣྛᐁ⬟ᇶࡢࣆ࣮ࢡࡀ␗࡞ࡿ໬Ꮫࢩࣇࢺ್࡟ฟ⌧ࡍࡿࡓࡵࡼࡾṇ☜࡞ゎᯒࡀྍ⬟࡛࠶ࡿࡀࠊࡑࡢឤᗘࡢపࡉ
࠿ࡽᚤ㔞࡞ᐁ⬟ᇶࡢほࡀᅔ㞴࡛࠶ࡗࡓࠋ㏆ᖺࠊNMRࡢឤᗘࢆᨵၿࡍࡿᡭἲ࡜ࡋ࡚ືⓗ᰾೫ᴟ(DNP)ࢆ฼⏝ࡋࡓDNP-NMRࡢ◊✲ࡀ⾜ࢃࢀ࡚࠸ࡿࠋDNP-NMR࡛ࡣ࣐࢖ࢡࣟἼ(MW)↷ᑕ࡟ࡼࡾࣛ
ࢪ࢝ࣝࡢ☢໬ࢆ᰾࡟⛣ࡍࡇ࡜࡛NMRࡢឤᗘࢆྥୖࡉࡏࡿࠋࡇࢀࡲ࡛Ⅳ⣲ᮦᩱࡢఏᑟᛶࡸ࣐࢖ࢡࣟ
Ἴ྾཰ࡣDNPຠᯝࢆῶᑡࡉࡏࡿࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠾ࡾ[1]ࠊDNP-NMRࢆ⏝࠸ࡓⅣ⣲ᮦᩱࡢ┤᥋ⓗ࡞
ほ ࡣ⾜ࢃࢀ࡚ࡇ࡞࠿ࡗࡓࠋࡋ࠿ࡋࠊDNP-NMR࡟ࡼࡿⅣ⣲⾲㠃ᐁ⬟ᇶࡢ┤᥋ⓗ࡞ほ ࡀྍ⬟࡟࡞
ࢀࡤⅣ⣲ᮦᩱ◊✲ࡢⓎᒎ࡟ࡘ࡞ࡀࡿࡓࡵࠊᮏ◊✲࡛ࡣGO࡜ࢫࢡ࣮ࣟࢫ⏤᮶Ⅳ⣲ࡢ⾲㠃ᐁ⬟ᇶࢆ
DNP-NMRࢆ⏝࠸࡚ほࡍࡿࡇ࡜࡛⾲㠃ᐁ⬟ᇶࡢゎᯒἲ࡜ࡋ࡚ࡢDNP-NMRࡢ᭷⏝ᛶࢆホ౯ࡋࡓࠋ࠙ᐇ㦂ࠚGOࡣBrodieἲ࡟ࡼࡾྜᡂࡋࡓࠋ㟁Ꮚࣞࣥࢪ࡛20 sຍ⇕ࡋ࡚๓ฎ⌮ࢆ⾜ࡗࡓ㯮㖄1 g࡟Ⓨ↮◪㓟20
mL࡜ሷ⣲㓟࣒࢝ࣜ࢘8 gࢆຍ࠼3᫬㛫᧠ᢾࡍࡿࡇ࡜࡛㓟໬ࢆ⾜ࡗࡓࠋ᧠ᢾᚋࠊỈ250 mLࢆຍ࠼ࠊୖ
⃈ࡳᾮࡢpHࡀ୰ᛶ࡟㏆࡙ࡃࡲ࡛㐲ᚰศ㞳ࢆ⧞ࡾ㏉ࡋGOࢧࣥࣉࣝ(Br-GO)ࢆᚓࡓࠋࢫࢡ࣮ࣟࢫ⏤᮶ѣႎఋ͞ಊఋᄬൢσᯚ, ᣠ҄᱅ᤲ, ἋἁἿὊἋဌஹ໗እ
‫࠿࡛ࡦ࠺࡝ࢇ࠶ۑ‬, ࡍࡎࡁ࠿ࡘ࠶ࡁ, ࠿ࡌࡦࢁࡢࡾ, ࡟ࡋ࡞ࡺ࠺ࡓ, ࠿ࢇ࡭ࡓ࠿ࡋ, ࡈ࡜࠺࠿ࡎࡲ

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Ⅳ⣲ᮦᩱࡣ❅⣲ὶ㏻ୗ࡟࠾࠸࡚┠ⓗ ᗘ(400ࠊ600ࠊ800 Υ)ࡲ࡛10 Υ/min࡛᪼ࡋ1᫬㛫ಖᣢࡍࡿࡇ࡜࡛స〇ࡋࡓ(௨㝆࡛ࡣྛࢧࣥࣉࣝࢆSuC-400ࠊSuC-600ࠊSuC-800࡜⾲グ)ࠋศᴟ๣࡜ࡋ࡚15 mM
AMUPol in D2O:H2O=9:1⁐ᾮࢆຍ࠼ࡓࢧࣥࣉࣝ࡜ຍ࠼࡚࠸࡞࠸ࢧࣥࣉࣝࢆ‽ഛࡋࠊྛࢧࣥࣉࣝࡢ
1

H-13C CPMAS DNP-NMR ᐃࢆ⾜ࡗࡓࠋࡲࡓྛⅣ⣲ࢧࣥࣉࣝࡢࣛࢪ࢝ࣝࡢ≧ែࢆ᥈ࡿࡓࡵ㟁Ꮚࢫࣆࣥඹ㬆(ESR) ᐃࢆ⾜ࡗࡓࠋ࠙⤖ᯝ࡜⪃ᐹࠚ
AMUPolῧຍBr-GO࡜AMUPolᮍῧຍBr-GOࡢ1H-13C CPMAS DNP-NMRࢫ࣌ࢡࢺࣝࢆFig. 1࡟♧ࡍࠋMW onࡢ࡜ࡁࠊAMUPolࢆῧຍࡍࡿࡇ࡜࡛55ࠊ66ࠊ126 ppmࡢࢩࢢࢼࣝᙉᗘࡀ⣙2.2ಸቑᙉࡋࡓࠋ
ࡇࢀࡽࡢࣆ࣮ࢡࡣࡑࢀࡒࢀ࢚࣏࢟ࢩᇶ(C-O-C)ࠊࣄࢻࣟ࢟ࢩᇶ(C-OH)ࠊsp2Ⅳ⣲࡟ᖐᒓࡉࢀࡿࠋࡲࡓࠊ
Ⅳ⣲ᮎ➃ࡢ࣓ࢳࣝᇶ(CH3)࡟ᖐᒓࡉࢀࡿ12 ppmࡢࣆ࣮ࢡ࡟㛵ࡋ࡚ࡢࡳ㧗࠸ቑᙉᗘࡀほ
AMUPolࢆῧຍࡋ࡞࠸ሙྜࡢ

ࡉࢀࡓࠋᐃࢆ⾜ࡗࡓ⤖ᯝࠊ๓⪅ࡢಙྕᙉᗘࡣMW↷ᑕ࡟ࡼࡗ࡚༙ῶࡋࡓ୍᪉ࠊ

ᚋ⪅ࡣAMUPolࢆῧຍࡋ࡞ࡃ࡚ࡶቑᙉࡉࢀ࡚࠸ࡓࠋESR ᐃ࠿ࡽࡣࠊBr-GOࡣࢧࣥࣉࣝෆ㒊࡟ࣛࢪ࢝ࣝࢆ᭷ࡍࡿࡇ࡜ࡀ☜ㄆ࡛ࡁࡓࠋࡇࢀࡽࡢᐇ㦂࠿ࡽ࢚࣏࢟ࢩᇶࠊࣄࢻࣟ࢟ࢩᇶࠊsp2Ⅳ⣲࡟ᑐࡋ࡚ࡣಙྕᙉᗘࡢቑᙉ࡟AMUPolࣛࢪ࢝ࣝࡀ኱ࡁࡃᐤ୚ࡍࡿ୍᪉ࠊCH3࡟ᑐࡋ࡚ࡣBr-GO⮬㌟ࡢෆ㒊ࣛࢪ࢝ࣝࡀ኱ࡁࡃᐤ୚ࡍࡿ࡜⪃࠼ࡽࢀࡿࠋ
AMUPolࢆῧຍࡋࡓྛࢫࢡ࣮ࣟࢫ⏤᮶Ⅳ⣲ࡢ1H-13C CPMAS DNP-NMRࢫ࣌ࢡࢺࣝࢆFig. 2࡟♧ࡍࠋྛࢧࣥࣉࣝࡣ150 ppm࡟=CR-OR’ (RࠊR’: HࡲࡓࡣⅣ໬Ỉ⣲ᇶ)࡟ᖐᒓࡉࢀࡿࢩࣙࣝࢲ࣮ᵓ㐀ࢆᣢࡘ
sp2Ⅳ⣲ࡢࣆ࣮ࢡࢆ♧ࡋࡓࠋࡲࡓࠊSuC-400࡜SuC-600࡟࠾࠸࡚ࡣMW onࡢ࡜ࡁࡢࡳ70 ppm௜㏆࡟COH࡟ᖐᒓࡉࢀࡿࣆ࣮ࢡࡀほࡉࢀࡓࠋC-OHࡢࣆ࣮ࢡࡣBr-GO࡟࠾ࡅࡿCH3 ࡢሙྜ࡜ࡣ␗࡞ࡾ

AMUPolᮍῧຍ᫬࡟ࡣᾘኻࡋࡓࠋ
ࡇࡢࡇ࡜࠿ࡽࠊࢫࢡ࣮ࣟࢫ⏤᮶Ⅳ⣲ࡢC-OHࡢಙྕᙉᗘቑᙉ࡟ࡣࢧ
ࣥࣉࣝ⮬㌟ࡢෆ㒊ࣛࢪ࡛࢝ࣝࡣ
࡞ࡃAMUPol⏤᮶ࡢࣛࢪ࢝ࣝࡀᐤ
୚ࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋࢫࢡࣟ
࣮ࢫ⏤᮶Ⅳ⣲࡟࠾࠸࡚C-OHࡢࢩࢢࢼࣝࡢࡳಙྕᙉᗘࡢቑᙉ⋡ࡀ኱ࡁ࠿ࡗࡓ⌮⏤࡜ࡋ࡚ࠊAMUPolࡣぶỈᛶ࡛࠶ࡿࡓࡵ࡟ぶỈᇶ࡛࠶ࡿC-OH࡜ᙉࡃ┦஫స⏝ࡋࡓࡓ

Fig. 1. 1H-13C CPMAS DNP-NMR spectra of Br-GO with
AMUPol (a) and without AMUPol (b). Spinning sidebands aremarked with asterisks.

ࡵ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ

Fig. 2. 1H-13C CPMAS DNP-NMR spectra of SuC-400 (a), SuC-600 (b) and SuC-800 (c) with AMUPol.
References[1] A. Svirinovsky-Arbeli, D. Rosenberg, D. Krotkov, R. Damari, K. Kundu, A. Feintuch, L. Houben, S.
Fleischer, M. Leskes, Solid State Nucl. Mag. Res. 99 (2019) 7-14.

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P77↓⣽⬊ྜᡂ⣔࡟ࡼࡿȕ2࢔ࢻࣞࢼࣜࣥཷᐜయⓎ⌧࡜ࡑࡢᵓ㐀࢔ࣥࢧࣥࣈࣝࡢᅛయNMRゎᯒ‫ۑ‬ᮡୗ཭᫭㸪⏣ᕳึ㸪ຍ⸨㈼㸪⸨ཎᩄ㐨㸪ᯇᮌ㝧1,21኱㜰኱Ꮫ࣭⺮ⓑ㉁◊✲ᡤ2኱㜰኱Ꮫ࣭㔞Ꮚ᝟ሗ࣭㔞Ꮚ⏕࿨◊✲ࢭࣥࢱ࣮

Expression of ȕ2-adrenergic receptor with cell-free synthesis and its conformational
ensemble analysis by solid-state NMR‫ۑ‬Tomoaki Sugishita1㸪Hajime Tamaki1㸪Ken Kato1㸪Toshimichi Fujiwara1,2㸪Yoh Matsuki1,2
1Institute for Protein Research, Osaka University

2 Center for Quantum Information and Quantum Biology, Osaka University

ȕ2-adrenergic receptor (ȕ2AR) is a model protein of G protein-coupled receptors, which has various
conformation associated with ligands and the following cascades. Solid-state NMR can be a powerful method
for the analysis of these conformational ensembles, which is important for the fundamental elucidation of the
GPCR signaling mechanisms. However, selective labeling is necessary for the ensemble analysis in order toavoid the peak congestion and increase the spectral resolution. Cell-free synthesis is a remarkable solution,
because it is not affected by cellular metabolism and cytotoxicity of additives. In this poster, we will
specifically present 77Se NMR measurements of selenomethionine-labeled ȕ2AR prepared by cell-freesynthesis, which is sensitive to the surrounding chemical environment and provide less peaks than othernuclei, and discuss the conformational ensemble of ȕ2AR based on their side-chain analysis.
࠙⫼ᬒ࣭┠ⓗࠚ G⺮ⓑ㉁ඹᙺᆺཷᐜయ㸦GPCR㸧ࡣᵝࠎ࡞ࣜ࢞ࣥࢻ࡜ࡑࡢ⤖ྜ࡟క࠺࢝ࢫࢣ࣮ࢻ࡟ࡼࡗ࡚ࠊከ✀ከᵝ࡞⏕⌮Ꮫⓗᶵ⬟࡟㛵୚ࡍࡿᕧ኱࡞⭷⺮ⓑ㉁ࣇ࢓࣑࣮࡛ࣜ࠶ࡿࠋ࡞࠿࡛ࡶȕ2-adrenergic receptor㸦ȕ2AR㸧ࡣGPCR◊✲ึᮇ࠿ࡽࡑࡢࣔࢹࣝ࡜ࡋ࡚ྲྀࡾୖࡆࡽࢀ࡚ࡁࡓ◊✲ᑐ㇟࡛࠶ࡾࠊ⤖ᬗᵓ㐀ゎᯒࠊࢡࣛ࢖࢜㟁Ꮚ㢧ᚤ㙾ࠊNMR࡜࠸ࡗࡓࠊከࡃࡢᡭἲ࡟ࡼࡗ࡚ྛ✀ࣜ࢞ࣥࢻ⤖ྜᆺࡢᵓ㐀ࡀᥦ♧ࡉࢀ࡚࠸ࡿࠋ≉࡟⁐ᾮNMRࡢ⤖ᯝ࠿ࡽࠊȕ2ARࡢᵓ㐀ኚ໬ࡣࣜ࢞ࣥࢻ࡜ᵓ㐀ࡀ1ᑐ1࡛ᑐᛂࡍࡿࡼ
࠺࡞༢⣧࡞ࣔࢹ࡛ࣝࡣ࡞ࡃࠊᐇ㝿࡟ࡣ࠸ࡃࡘ࠿ࡢࢥࣥࣇ࢛࣓࣮ࢩࣙࣥ㛫࡛ᵓ㐀ᖹ⾮ࡀᏑᅾࡋ࡚࠸
ࡿࡇ࡜ࡀ♧၀ࡉࢀ࡚࠸ࡿ[1]ࠋࡋ࠿ࡋࠊࡑࢀࡒࢀࡢࣜ࢞ࣥࢻ⤖ྜ≧ែ࡟࠾࠸࡚ȕ2ARࡀ඲య࡜ࡋ࡚࡝
ࡢࡼ࠺࡞ᵓ㐀࢔ࣥࢧࣥࣈࣝࢆࡶࡗ࡚࠸ࡿ࠿ࠊᐃ㔞ⓗ࡞ホ౯ࡣ㞴ࡋࡃࠊᮍࡔࡑࡢヲ⣽ࡣ୙࡛᫂࠶ࡿࠋ
 ᅛయNMRࡣ⺮ⓑ㉁ࡢᵓ㐀࢔ࣥࢧࣥࣈࣝゎᯒ࡟฼⏝࡛ࡁࡿ࣏ࢸࣥࢩࣕࣝࡣ࠶ࡿࡶࡢࡢࠊపឤᗘࠊ
పศゎ⬟࡜࠸࠺ᢏ⾡ⓗไ⣙࡟ࡼࡗ࡚ᚑ᮶ࡑࡢᛂ⏝ඛࡣ㝈ᐃⓗ࡛࠶ࡗࡓࠋ㏆ᖺࡣ㧗☢ሙືⓗ᰾ศᴟ㸦DNP㸧ࡸ㧗㏿࣐ࢪࢵࢡゅヨᩱᅇ㌿㸦MAS㸧ࡢⓎᒎ࡟ࡼࡾࠊឤᗘ࠾ࡼࡧศゎ⬟ࡢၥ㢟ࡀ኱ᖜ࡟ᨵ
ၿࡉࢀࡘࡘ࠶ࡿࠋࡑࡢ⤖ᯝࠊ௒ࡲ࡛ࡣࢫ࣌ࢡࢺࣝ⥺ᙧࡀᗈᖜ࡟࡞ࡾឤᗘ୙㊊࡛ᐃ࡛ࡁ࡞࠿ࡗࡓ

⺮ⓑ㉁ࡢ࣐࢖ࢼ࣮࡞ࢥࣥࣇ࢛࣓࣮ࢩࣙࣥᡂศࢆᥒ࠸ྲྀࡿࡇ࡜ࡀ࡛ࡁࡿࡼ࠺࡟࡞ࡗ࡚ࡁࡓ[2]ࠋ
ࡓࡔࡋMAS࡟ࡼࡿศゎ⬟ྥୖࢆ⪃៖ࡋ࡚ࡶࠊ≉࡟ᵓ㐀࢔ࣥࢧࣥࣈࣝࡀ࠶ࡿࡼ࠺࡞⣔࡛ࡣࣆ࣮ࢡ
ΰ㞧ࡀ㑊ࡅࡽࢀ࡞࠸ࠋࡋࡓࡀࡗ࡚ࠊࢧࣥࣉࣝㄪ〇᫬ࡢ㑅ᢥᶆ㆑ࢹࢨ࢖ࣥࡀ㔜せ࡟࡞ࡿࠋࡇࡇ࡛ၥ
㢟࡜࡞ࡿࡢࡀࠊGPCRࡢⓎ⌧ࡀ୍㒊ࡢ౛እࢆ㝖࠸࡚ࠊᇶᮏⓗ࡟᪻⹸⣽⬊ࡸ့ங⣽⬊➼ࡢ㧗ḟⓎ⌧
ᅛయNMR㸪↓⣽⬊ྜᡂ㸪GPCR‫ࡁ࠶ࡶ࡜ࡓࡋࡂࡍۑ‬㸪ࡓࡲࡁࡣࡌࡵ㸪࠿࡜࠺ࡅࢇ㸪ࡩࡌࢃࡽ࡜ࡋࡳࡕ㸪ࡲࡘࡁࡼ࠺

－ 304 －

⣔࡟㝈ࡽࢀࡿⅬ࡛࠶ࡿࠋ㧗ḟⓎ⌧⣔࡛ࡣ࢔࣑ࣀᇶ㌿⛣㓝⣲➼࡟ࡼࡿ௦ㅰࡢ㛵ಀ࡛ᶆ㆑࡛ࡁࡿ࢔࣑
ࣀ㓟ࡀไ㝈ࡉࢀࡿࠋࡑࡢⅬ࡟࠾࠸࡚ࠊ↓⣽⬊ྜᡂ⣔ࡣ࢔࣑ࣀ㓟௦ㅰ࡟ࡼࡿࢫࢡࣛࣥࣈࣜࣥࢢࡀ㉳ࡇࡽࡎࠊ௵ពࡢ㑅ᢥᶆ㆑ࢆ⾜࠺ࡇ࡜ࡀྍ⬟࡛࠶ࡿࠋࡲࡓᶆⓗ⺮ⓑ㉁ࡸῧຍ๣࡟⣽⬊ẘᛶࡀ࠶ࡿሙ
ྜ࡛ࡶၥ㢟ࡀ࡞࠸ࠋࡋࡓࡀࡗ࡚NMR ᐃ⏝ࡢGPCRࡢࢧࣥࣉࣝㄪ〇࡟㐺ࡋࡓ⣔࡛࠶ࡿ࡜࠸࠼ࡿࠋ
⌧ᅾࠊȕ2ARࡢᶵ⬟࡜㛵㐃ࡍࡿᵓ㐀࢔ࣥࢧࣥࣈࣝ࡟ࡘ࠸࡚ከゅⓗ࡟ศᯒࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡋ࡚ࠊ↓⣽⬊ྜᡂ⣔࡟ࡼࡿ࢔࣑ࣀ㓟㑅ᢥᶆ㆑ȕ2ARࢧࣥࣉࣝࢆ㧗☢ሙᴟప

DNP-NMRᐃࡍࡿࡇ࡜࡟ࡼ

ࡗ࡚ᚓࡽࢀࡿ୺㙐᝟ሗࡢゎᯒ࡜ࠊࢭࣞࣀ࣓ࢳ࢜ࢽࣥᶆ㆑ȕ2ARࡢ㧗㏿MAS-NMRᐃ࡟ࡼࡿഃ㙐᝟ሗࡢゎᯒࢆ୧㍯࡜ࡋ࡚◊✲ࢆ㐍ࡵ࡚࠸ࡿࠋ≉࡟ࠊ௒ᅇࡢⓎ⾲࡛ࡣᚋ⪅ࡢࢭࣞࣀ࣓ࢳ࢜ࢽࣥᶆ㆑
ȕ2AR ࡢ77Se ᐃ࡟ࡘ࠸࡚㆟ㄽࡍࡿணᐃ࡛࠶ࡿࠋ
࠙⺮ⓑ㉁Ⓨ⌧࣭⢭〇ࠚ኱⭠⳦⏝࡟ࢥࢻࣥ᭱㐺໬ࡋࡓȕ2ARࡢDNA㓄ิ࡟ᑐࡋࠊNᮎ➃࡟HATࢱࢢࠊCᮎ➃࡟࢙࢘ࢫࢱࣥ
ࣈࣟࢵࢺ᳨ฟ⏝ࡢFLAGࢱࢢࢆᑟධࡋࡓࠋࡇࡢ┤㙐DNAࢆPCR࡛ቑᖜࡋࠊ↓⣽⬊ྜᡂࡢࢸࣥࣉ࣮ࣞ
ࢺ࡜ࡋ࡚౑⏝ࡋࡓࠋ኱⭠⳦⏤᮶ࡢ↓⣽⬊཯ᛂᾮ㸦኱㝧᪥㓟㸧࡟ࢭࣞࣀ࣓ࢳ࢜ࢽࣥྵ᭷࢔࣑ࣀ㓟ᾮࢆῧຍࡋ࡚↓⣽⬊ྜᡂࢆ⾜ࡗࡓࠋྜᡂᚋࠊ཯ᛂᾮࢆTALONࣞࢪ࡛ࣥ࢔ࣇ࢕ࢽࢸ࢕⢭〇ࡋࠊTEVࣉࣟࢸ࢔࣮ࢮ࡛Nᮎ➃ࡢHATࢱࢢࢆษ᩿ࡋࡓᚋࠊࢤࣝࢁ㐣⢭〇ࢆ⾜ࡗࡓࠋ⬡㉁⭷㸦DOPC㸧࡜ࢥࣞࢫࢸ࣮ࣟࣝ㸦ࢥࣞࢫࢸ࣑ࣜࣝ࣊ࢥࣁࢡ㓟㸧ࡀ10:1㸦w/w㸧࡛⤌ᡂࡉࢀࡓ࣏ࣜࢯ࣮࣒࡟ᑐࡋࠊ⢭〇ࡋࡓ
ȕ2ARࢆ෌ᵓᡂࡋࡓࠋ
࠙ࢭࣞࣀ࣓ࢳ࢜ࢽࣥᅛయNMR ᐃࠚ
77Seࡣࢫࣆࣥ1/2ࢆࡶࡘ᰾✀࡛ࠊ◲㯤࡜ྠ᪘࡛࠶ࡾᛶ㉁ࡶࡼࡃఝ࡚࠸ࡿ୍᪉࡛ࠊ◲㯤ࡢᏳᐃྠ఩య33S࡜ẚ㍑
ࡋ࡚ඹ㬆࿘Ἴᩘࡸኳ↛ᏑᅾẚࠊᅄᴟᏊ┦஫స⏝ࡢ᭷↓ࡢほⅬ࠿ࡽNMRほ࡟㐺ࡋ࡚࠸ࡿࡓࡵࠊࡋࡤࡋࡤ◲㯤ࡢ௦ࢃࡾ࡟⺮ⓑ㉁࡟ᑟධࡉࢀࠊNMR ᐃ࡟⏝࠸ࡽࢀࡿࠋ
ணഛᐇ㦂࡜ࡋ࡚ࠊࢭࣞࣀ- L-࣓ࢳ࢜ࢽࣥࡢᚤ⤖ᬗ⢊ᮎࡢᅛయNMR ᐃࢆ⾜ࡗࡓࠋ1Hඹ㬆࿘Ἴᩘ700 MHz㸦77Se
ඹ㬆࿘Ἴᩘ133.5 MHz㸧ࡢNMRศගィࢆ౑⏝ࡋࠊMAS㏿
ᗘ70 kHzࠊ338 K࠾ࡼࡧ288 Kࡢ᮲௳࡛⾜ࡗࡓ1H-77Seࡢ2
ḟඖdouble-CP ᐃࡢ⤖ᯝࢆ♧ࡍ㸦Fig.1㸧ࠋ338 K࡛ࡣ111
ppm࡟1ᮏࡢࣆ࣮ࢡࡀᚓࡽࢀࡓࡀࠊ288 K࡛ࡣ119 ppm࡜76 ppm࡟ࡑࢀࡒࢀ⥺ᖜࡢ␗࡞ࡿ2ࡘࡢࣆ࣮ࢡࡀᚓࡽࢀ
ࡓࠋࡇࡢ⤖ᯝࡣPotrzebowskiࡽࡢࠊ⤖ᬗᵓ㐀୰࡟ࢭࣞࣀ

Fig. 1. 77Se-NMR spectra of seleno-Lmethionine microcrystalline powder.
Two spectra were provided with 1H-77Se
2D double-CP at 338 K and 288 K.

࣓ࢳ࢜ࢽࣥࡢࢥࣥࣇ࢛࣓࣮ࢩࣙࣥࡀ2ࡘᏑᅾࡍࡿ࡜࠸࠺ሗ࿌[3]࡜୍⮴ࡍࡿ⤖ᯝ࡛࠶ࡾࠊ288 Kࡢࢫ࣌ࢡࢺࣝ࡟࠾ࡅࡿ2ࡘࡢࣆ࣮ࢡࡣࠊࡇࡢ2ࡘࡢᵓ㐀ࢆ཯ᫎࡋ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ୍᪉ࠊ338 K࡛ࡣ⇕ᦂࡽࡂࡢᙳ㡪࡛ࠊࡇࢀࡽ2ࡘࡢᖹᆒᵓ㐀࡜ࡋ࡚1ᮏࡢࣆ࣮ࢡࡀᚓࡽࢀࡓࡶࡢ࡜⪃࠼ࡽࢀࡿࠋ77Seࡢ
໬Ꮫࢩࣇࢺࡣ≉࡟࿘㎶ࡢ໬Ꮫⓗ⎔ቃ࡟㗦ᩄ࡛࠶ࡿࡓࡵࠊࢭࣞࣀ࣓ࢳ࢜ࢽࣥᶆ㆑ࡋࡓȕ2AR࡟࠾࠸࡚ࡶࠊࡑࡢࢥࣥࣇ࢛࣓࣮ࢩࣙࣥኚ໬ࡀ㆟ㄽ࡛ࡁࡿ࡜ᮇᚅࡉࢀࡿࠋ
References[1] Kofuku et al. (2012), Nature communication, 3, 1045.
[2] Takamuku et al. (2022), Neurochemistry International, 157, 105345.
[3] Gajda et al. (2006), Jornal of Physical Chemistry B, 110, 25692.

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P78Y

඲ᅛయ㟁ụࡢ㧗ឤᗘ࢜࣌ࣛࣥࢻィ




ἲࡢ㛤Ⓨ



‫ۑ‬ᅄ᪉Ṍ⨾ 㸪⏣ୖಟ 㸪⸨ཎ൉ᖹ 㸪㧗ᶫ຾ᅧ㸪ᑎす㈗ᚿ㸪➃೺஧㑻㸪
⸨ᡞ㍤᫛㸪ရᕝ⚽⾜㸪ᚋ⸨࿴㤿1ᒸᒣ኱Ꮫ኱Ꮫ㝔 ⮬↛⛉Ꮫ◊✲⛉2≀㉁࣭ᮦᩱ◊✲ᶵᵓ
3ᰴᘧ఍♫ࣉ࣮ࣟࣈᕤᡣ

Development of a high-sensitive operando NMR for all-solid-state batteries‫ۑ‬Ayumi Shikata1, Osamu Tagami1, Ryouhei Fujiwara1, Masakuni Takahashi1, Takashi Teranishi1, Kenjiro
Hashi2, Teruaki Fujito3, Hideyuki Shinagawa3, Kazuma Gotoh1
1 Graduate school of natural science and technology, Okayama University
2 National Institute for Materials Science3 PROBE LAB. INC.

All-solid-state lithium-ion battery (ASSLB) is one of the most promising next-generation second
batteries which has high safety and high energy density. However, a problem of deactivation which is
caused by the deposition of dendritic lithium inside the battery during high-speed charging and discharging
hasn’t been settled. To solve the problem, it is required to clarify the charge-discharge behavior and tounderstand the deactivation mechanism. In this study, a handmade ASSLB and a probe were developed torealize operando 7Li NMR to observe the dendritic lithium. Lithium-ion insertion process into hard carbon
electrode in ASSLB was observed using operando 7Li NMR.
࠙⥴ゝࠚࣜࢳ࣒࢘࢖࢜ࣥ㟁ụࡣࢫ࣐࣮ࢺࣇ࢛ࣥࡸࣀ࣮ࢺᆺࣃࢯࢥࣥࡢ㟁※࡜ࡋ࡚ᗈࡃ฼⏝ࡉࢀ㸪㟁Ẽ⮬ື㌴࡬ࡢᦚ㍕ࡸ㟁ຊ㈓ⶶ┠ⓗ࡛ࡢ౑⏝ࡶᗈࡀࡗ࡚࠸ࡿ㸬≉࡟඲ᅛయࣜࢳ࣒࢘࢖࢜ࣥ㟁ụ඲ᅛయ㟁ụ ࡣᏳ඲࠿ࡘ㧗ᐜ㔞࡞㟁ụ࡜ࡋ࡚௒ᚋࡢᐇ⏝໬ࡀᮇᚅࡉࢀ࡚࠸ࡿࡀ㸪㧗㏿඘ᨺ㟁᫬࡟㟁ụෆ㒊࡟㔪ᶞ≧㔠ᒓࣜࢳ࣒࢘ ࢹࣥࢻࣛ࢖ࢺ ࡀᯒฟࡋኻάࡋ࡚ࡋࡲ࠺࡜࠸࠺ၥ㢟ࡀᮍゎỴ࡛࠶ࡾ㸪ࡑࡢ඘ᨺ㟁ᶵᵓࡸኻά࣓࢝ࢽࢬ࣒ࡢ
ゎ᫂ࡀồࡵࡽࢀ࡚࠸ࡿ㸬ᮏ◊✲࡛ࡣ㸪ࣜࢳ࣒࢘ࢹࣥࢻࣛ࢖ࢺࡢ┤᥋ほ ࡀྍ⬟࡞
7Li NMR࡟ࡼࡿ㟁ụࡢ㧗ឤᗘ࢜࣌ࣛࣥࢻ

ィࢆᐇ⌧ࡍࡿࡓࡵ㸪඲ᅛయ㟁ụ⏝ࢭࣝ࡜ࣉ࣮ࣟࣈࢆస〇ࡋ㸪Ⅳ⣲㈇ᴟ࡬ࡢLi྾ⶶ㐣⛬ࢆほ ࡋࡓ㸬Fig.1 Structure of the cell and the probe࠙ᐇ㦂ࠚAr㞺ᅖẼୗࡢࢢ࣮ࣟࣈ࣎ࢵࢡࢫෆ
࡛PEEKᮦ〇ࡢࣉࣛࢫࢳࢵࢡࢭࣝࣃࢵࢣ࣮ࢪ㸪స⏝㟁ᴟ ࣁ࣮ࢻ࣮࢝࣎ࣥ㸪Carbotron®P(J))㸪◲໬≀⣔ᅛయ㟁ゎ㉁(Li6PS5Cl㸪NEI Corp.)㸪ᑐᴟ(㔠ᒓࣜࢳ࣒࢘⟩)࡛ᵓᡂࡉࢀࡿ༙㟁ụ(Fig.1)ࢆస〇ࡋࡓ㸬స⏝㟁ᴟ࡜ᅛయ㟁ゎ㉁ࡣȭ8.0 mmࡢ෇ᙧ2ᒙ㟁ᴟ࣌ࣞࢵࢺ࡜ࡋࡓ㸬
7Li NMR㸪࢜࣌ࣛࣥࢻィ㸪඲ᅛయࣜࢳ࣒࢘࢖࢜ࣥ㟁ụ‫ࡳࡺ࠶ࡓ࠿ࡋۑ‬㸪ࡓࡀࡳ࠾ࡉࡴ㸪ࡩࡌࢃࡽࡾࡻ࠺࡬࠸㸪ࡓ࠿ࡣࡋࡲࡉࡃ࡟㸪࡚ࡽ࡟ࡋࡓ࠿ࡋ㸪  ࡣࡋࡅࢇࡌࢁ࠺㸪ࡩࡌ࡜࡚ࡿ࠶ࡁ㸪ࡋ࡞ࡀࢃࡦ࡛ࡺࡁ㸪ࡈ࡜࠺࠿ࡎࡲ

－ 306 －

7

Li NMRࢫ࣌ࢡࢺࣝࡢ ᐃ࡟ࡣAgilent DD2 spectrometer(11.7 T)࠾ࡼࡧ㟁ὶ༳ຍᅇ㊰௜ࣉ࣮ࣟࣈࢆ

⏝࠸ࡓ㸬 ᐃ᮲௳ࡣࢩࣥࢢࣝࣃࣝࢫ⣔ิ㸪ࢫࣆ࣭࢚ࣥࢥ࣮ἲ࡟ࡼࡿࢫ࣌ࢡࢺࣝࡢྲྀᚓ㸪✚⟬ᅇᩘ
128ᅇ㸪 ᐃ᫬ ᗘ23Υ࠾ࡼࡧ60Υ࡜ࡋࡓ㸬㟁ụ㟁ᴟ㠃ࡀእ㒊☢ሙࡢྥࡁ࡟ᑐࡋ࡚90r࡟࡞ࡿࡼ࠺㟁ụࢆࢭࢵࢺࡋ㸪ୗ㝈㟁ᅽࢆ0 V࡜ࡋࡓᐃ㟁ὶᐃ㟁ᅽᨺ㟁(Liᤄධ)࠾ࡼࡧୗ㝈㟁ᅽࢆ㸫1.0 V࡜ࡋࡓ㐣ᨺ㟁ࡢ㝿ࡢ඲ᅛయ㟁ụࡢෆ㒊ኚ໬ࢆࣜ࢔ࣝࢱ࢖࣒࡛ほ ࡋࡓ㸬࠙⤖ᯝ࣭⪃ᐹࠚ
ᗘ23Υ࣭඘ᨺ㟁㏿
ᗘ0.05 C࡛㸪ୗ㝈㟁ᅽࢆ㸫1.0 V࡜ࡋࡓ㐣ᨺ㟁
(overdischarge)ࢆ⾜ࡗࡓ㟁ụ࡛ࡣ㸪ᨺ㟁㛤ጞ࠿ࡽ2.5᫬㛫࡯࡝࡛⏺㠃཯ᛂ࡟
ࡼࡿศゎ⏕ᡂ≀ࡢࣆ࣮ࢡࡢฟ⌧࣭ቑຍࡀほ ࡉࢀࡓ
(Fig.2㸪୸༳)㸬ᨺ㟁ࡢ⤊┙(0 V฿㐩

Fig.2 Charge-discharge curve and the corresponding operando 7Li NMR spectra
Υ, 0.05C overdischarge)(23Υ࠿ࡽ⣙6᫬㛫ᚋ)࡛
60㹼120 ppm࡟ᖜᗈ࠸ࣆ࣮ࢡࡀほ ࡉࢀࡓ㸬ࡇࡢࣆ࣮ࢡࡣࣁ࣮ࢻ࣮࢝࣎ࣥ㟁ᴟ࡟ᤄධࡉࢀᙧᡂࡉ
ࢀࡓࣜࢳ࣒࢘ࢡࣛࢫࢱ࣮࡟ᖐᒓࡉࢀࡿ㸬ࢹࣥࢻࣛ࢖ࢺࣆ࣮ࢡࡣほ ࡉࢀ࡞࠿ࡗࡓࡀ㸪ࡑࡢᚋ᭦࡟
㐣ᨺ㟁ࢆ⾜࠸㟁ụࡀ▷⤡ࡋࡓ≧ែ࡛ࡣࢹࣥࢻࣛ࢖ࢺ≧ࣜࢳ࣒࢘࡟ᖐᒓࡉࢀࡿ278.2 ppmࡢࣆ࣮ࢡࡀほ ࡉࢀࡓ㸬
ᗘ60Υ࣭඘ᨺ㟁㏿ᗘ0.1 C࡛㸪0 Vࡲ࡛ᐃ㟁ὶᨺ㟁ࡑࡢᚋᐃ㟁ᅽᨺ㟁(CCCV
discharge)ࢆ⾜ࡗࡓ㟁ụ࡛ࡣ㸪0 V฿㐩᫬ࡢᐜ㔞ࡀ364.5 mAh g-1࡜኱ࡁࡃఙࡧ㸪᫂░࡞ศゎ⏕ᡂ≀ࣆ࣮ࢡࡣほ ࡉࢀ࡞࠿ࡗࡓ㸬ࡇࡢ㟁ụ࡛ࡶᨺ㟁ࡢ⤊┙(0 V฿㐩࠿ࡽ⣙4᫬㛫ᚋ)࡛ࣁ࣮ࢻ࣮࢝࣎ࣥ㟁ᴟෆ࡟ᙧᡂࡉ
ࢀࡓࣜࢳ࣒࢘ࢡࣛࢫࢱ࣮ࡢᖜᗈ࠸ࣆ࣮ࢡ
(60㹼120 ppm)ࡀほ ࡉࢀࡓ(Fig.3)㸬
ᮏ◊✲࡛ࡣ࢜࣌ࣛࣥࢻィ ࢆᐇ⌧ࡍࡿ≉Ṧᆺ඲ᅛయ㟁ụࡢస〇࡟ᡂຌࡋ㸪ᐊ ࠾ࡼࡧ㧗 (60Υ)࡟࡚඲ᅛయ㟁ụࡢᨺ㟁᫬ࡢ

Fig.3 A 7Li NMR spectrum in operando measurement(60Υ
Υ, after 0.1C CCCV discharge)
ෆ㒊ኚ໬(ศゎ⏕ᡂ≀㸪ࢡࣛࢫࢱ࣮㸪ࢹࣥࢻࣛ࢖ࢺ)ࢆほ ࡍࡿࡇ࡜ࡀ࡛ࡁࡓ㸬－ 307 －

P79Ỉ⣲஺᥮㏿ᗘほࢆ฼⏝ࡋࡓࣇ࢓࣮࣐ࢥࣇ࢛࢔ゎᯒࡢヨࡳ‫ۑ‬ᰩ⏣㡰୍  ᖹᑿඃె すᮧၿᩥ
ᶓ὾ᕷ❧኱Ꮫ⏕࿨་⛉Ꮫ◊✲⛉ᗈᓥ኱Ꮫ኱Ꮫ㝔⤫ྜ⏕࿨⛉Ꮫ◊✲⛉

Pharmacophore analysis using hydrogen exchange rates
żJun-ichi Kurita1, Yuuka Hirao1, Yoshifumi Nishimura1,2
1

Graduate school of medical life science, Yokohama City University

2

Graduate school of integrated sciences for life, Hiroshima UniversityCurrently, NMR is used as a tool for screening and analyzing drug candidates in various stagesof drug discovery. Although widely used chemical shift perturbation experiments are very
effective for analyzing interactions of compounds with a target protein , in the case of a flexible
target protein, chemical shift changes themselves are also sensitive to the protein conformationalchanges caused by binding to a compound and it is too difficult to identify the interaction site in
the protein. The well-known saturation transfer method has been applied to relatively large
molecular weight complexes with efficient spin diffusions, such as protein-protein interactions,but is not easily applied to the interaction of small proteins with small molecular ligands, inaddition sample preparations such as deuterium labeling technique is hardly to be applied. Here,
we attempted to use hydrogen exchange rates in a flexible target protein , which is possiblylabelled even with only relatively inexpensive 15 N stable isotope, and to apply the interaction siteanalysis of the target with some ligands.

ࡣࡌࡵ࡟105ࡣ ๰ ⸆ ࡢ ᵝ ࠎ ࡞ ࢫ ࢸ ࣮ ࢪ ࡛ ྜ ᡂ ☜ ㄆ ࡢ ࡳ ࡞ ࡽ ࡎ ࢫ ࢡ ࣜ ࣮ ࢽ ࣥ ࢢ ࡸ ࢱ ࣥ ࣃ ࢡ ㉁ ࡜ ࣜ࢞ࣥࢻࡢ┦஫స⏝ゎᯒ࡟࠾࠸࡚࡞ࡃ࡚ࡣ࡞ࡽ࡞࠸ࢶ࣮ࣝ࡜ࡋ࡚⌧ᅾ౑ࢃࢀ࡚࠾ࡾࠊ┦஫స⏝ゎᯒ࡛ࡣ⁲ୗᐇ㦂࡟ࡼࡿ໬Ꮫࢩࣇࢺኚ໬ࡢほࡀᗈࡃ⾜ࢃࢀ࡚࠸ࡿࠋࡇࡢᡭἲ

ࡣ㘽࡜㘽✰ࡢࡼ࠺࡞┦஫స⏝ࡢゎᯒ࡟ࡣ 㠀ᖖ࡟᭷ຠ࡛ࡣ࠶ࡿࡶࡢࡢࠊ໬Ꮫࢩࣇࢺኚ໬
⮬యࡀࢱࣥࣃࢡ㉁ࡢᵓ㐀ኚ໬࡟ࡶᩄឤ࡛࠶ࡿⅭ࡟ ᰂ㌾࡞ࢱࣥࣃࢡ㉁࡜ࣜ࢞ࣥࢻࡢ┦஫స⏝ࡢᵝ࡞ሙྜࡣ┦஫స⏝㒊఩ࢆ≉ᐃࡍࡿࡇ࡜ࡣᅔ㞴࡛࠶ࡿࠋࢱࣥࣃࢡ㉁࡜ࢱࣥࣃࢡ㉁ࡢ┦஫స⏝ࡢᵝ࡟ࢫࣆࣥᣑᩓࡀຠ⋡ࡼࡃ㐍ࡴࡼ࠺࡞ ẚ㍑ⓗศᏊ㔞ࡀ኱ࡁ࠸⣔࡛ࡣ㣬࿴⛣ືἲࡢࡼ࠺࡞ࢫ࣐࣮ࢺ࡞᪉ἲࢆ㐺ᛂࡍࡿࡇ࡜ࡀ࡛ࡁࡿࡀࠊᑠࡉ࡞ࢱࣥࣃࢡ㉁࡜ప
ศᏊࣜ࢞ࣥࢻࡢࡼ࠺࡞⣔࡛ࡣ㐺⏝ࡀ㞴ࡋࡃࠊ᭦࡟㔜Ỉ⣲ࣛ࣋ࣝࡀᚲせ࡛࠶ࡿࡇ࡜࡞࡝
ヨ ᩱ ㄪ 〇 ࡢ ࣁ ࣮ ࢻ ࣝ ࡀ 㧗 ࠸ ࠋ ࡑ ࡇ ࡛ ᡃ ࠎ ࡣ ࠊ  1Ᏻ ᐃ ྠ ఩ య ᶆ ㆑ ࡢ ࡳ ࡛ ⾜ ࠼ ࡿ Ỉ ⣲ ஺ ᥮㏿ᗘࢆほࡋࠊࡑࡢኚ໬ࢆ┦஫స⏝ゎᯒ࡟ᛂ⏝ࡍࡿࡇ࡜ࢆヨࡳࡓࠋ᪉ἲ ࢱ࣮ࢤࢵࢺࢱࣥࣃࢡ㉁P6LQ$3$+ࢻ࣓࢖ࣥ X0ࢫࢡ࣮ࣜࢽࣥࢢ࡟ࡼࡾ㑅ᢤࡉࢀࡓ໬ྜ≀'ࢆ࡟࡞ࡿࡼ࠺࡟S+P0ࣜࣥ㓟ࣂࢵࣇ࢓࣮ '2 ࡟⁐ゎࡋヨᩱ࡜ࡋࡓࠋ105ࢫ࣌ࢡࢺࣝ
ࡢ

ᐃ࡟ࡣ&U\R7&,)ࢆ⿦ഛࡋࡓ$9$1&(,,,+'0+] %58.(5♫〇 ࢆ⏝࠸࡚ࠊ+(7H[7526<ἲ࡟ࡼࡾỈ⣲஺᥮㏿ᗘࢆほ ࡋࡓࠋࢱࣥࣃࢡ㉁ࠊࣜ࢞ࣥࢻ
‫ࡳࡩࡋࡼ ࡽࡴࡋ࡟ࠊ࠿࠺ࡺ ࠾ࡽࡦࠊࡕ࠸ࢇࡹࡌ ࡓࡾࡃۑ‬－ 308 －

ᅗ 1. ໬ྜ≀ D5 ࡢ⤖ྜ࡟ࡼࡿ Sin3A PAH1 ࢻ࣓࢖ࣥࡢ CSP(ୖ)࡜Ỉ⣲஺᥮㏿ᗘኚ໬(ୗ)ࡢẚ㍑⤖ᯝ࡜⪃ᐹ
Sin3A PAH1ࢻ࣓࢖ࣥࡣ໬ྜ≀D5࡜ࡢ⤖ྜ࡟ࡼࡾࢻ࣓࢖ࣥ඲య
ࡢ໬Ꮫࢩࣇࢺࡀኚ໬ࡋ࡚࠾ࡾᒁᡤ
ⓗ࡞ኚ໬ࡢ≉ᐃࡀᅔ㞴࡛࠶ࡿࡀࠊ
Ỉ⣲஺᥮㏿ᗘࡣᒁᡤⓗ࡞ኚ໬ࡀほࡉࢀ࡚࠸ࡿ(ᅗ1)ࠋࡲࡓࡑࢀࡒࢀ
ࡢᐇ㦂࡟࠾࠸࡚ኚ໬ࡢᖹᆒ್࠿ࡽ
Ȫࡼࡾࡶ኱ࡁ࠸ኚ໬ࢆぢࡏࡓṧᇶࢆactive residue࡜ࡋ࡚HADDOCK࡟ࡼࡿࢻࢵ࢟ࣥࢢࢆ⾜ࡗࡓ⤖ᯝࢆᅗ2࡟♧ࡍࠋCSPࡣᰂ㌾࡞㒊఩ࡀ኱ࡁ࡞ኚ໬ࢆぢࡏࡿഴྥࡀ࠶
ࡿⅭࠊࢸ࣮ࣝ௜㏆࡟⤖ྜࡋ࡚࠸ࡿ

ᅗ 2. CSP ᝟ሗࢆ฼⏝ࡋࡓࢻࢵ࢟ࣥࢢᵓ㐀㸦ᕥ㸧Ỉ⣲஺᥮㏿ᗘኚ໬ほ ࢆ฼⏝ࡋࡓࢻࢵ࢟ࣥࢢᵓ㐀(ྑ)ࡼ࠺࡟ゎᯒࡉࢀ࡚ࡋࡲ࠺ࡀࠊỈ⣲஺᥮㏿ᗘኚ໬ࢆ⏝࠸ࡓゎᯒ࡛ࡣࡼࡾ࣏ࢣࢵࢺ࡟ධࡗࡓ⤖ྜᵝᘧ࡟ゎᯒࡉࢀࡓࠋࡇࡢ⣔࡛ࡣ13C15NᏳᐃྠ఩యᶆ㆑ࢧࣥࣉࣝࢆ⏝࠸ࡿࡇ࡜࡟ࡼࡗ࡚࣏ࢣࢵࢺዟ࡟Ꮡ
ᅾࡍࡿV46ࡸI47࠿ࡽࡢศᏊ㛫NOEࢆほ ࡍࡿࡇ࡜ࡀ࡛ࡁࡓࡓࡵࠊỈ⣲஺᥮㏿ᗘほ ࢆ⏝࠸ࡓゎᯒ࡟ࡼࡿ」ྜయᵓ㐀ࡀᨭᣢࡉࢀࡓࠋࡇࢀࡣᮏᡭἲࡢጇᙜᛶࢆ♧ࡍࡶࡢ࡛࠶ࡿࠋ
(1) Rennella, E., Solyom, Z., and Brutscher, B. (2014) Measuring hydrogen exchange in proteins by selective
water saturation in 1H- 15N SOFAST/BEST-type experiments: advantages and limitations. J. Biomol. NMR 60,
99–107.

－ 309 －

P80Y

ඹᬗἲ䛻䜘䜛⏕యศᏊ䛾㼀㼞㼕㼜㼘㼑㼠㻌㻰㻺㻼㻌ࠐబ⸨ᬕ⣖ᐑすᏕ୍㑻᰿᮶ㄔ㤶ᕝ᫭ᚨすᒣ⿱௓୰ᮧᾈ
୍≟㣫᐀ᘯᚨᓥ኱Ꮫ኱Ꮫ㝔 ๰ᡂ⛉Ꮫ◊✲⛉኱㜰኱Ꮫ኱Ꮫ㝔 ᇶ♏ᕤᏛ◊✲⛉ ኱㜰኱Ꮫ㔞Ꮚ᝟ሗ࣭㔞Ꮚ⏕࿨◊✲ࢭࣥࢱ࣮

㔞Ꮚ⛉Ꮫᢏ⾡㛤Ⓨᶵᵓ㔞Ꮚ⏕࿨⛉Ꮫ◊✲ᡤ⌮◊-(2/㐃ᦠࢭࣥࢱ࣮ ᰴᘧ఍♫-(2/5(621$1&(ᚨᓥ኱Ꮫ኱Ꮫ㝔 ♫఍⏘ᴗ⌮ᕤᏛ◊✲㒊Hyperpolarization of Biomolecules in eutectic crystals using Triplet DNPࠐHaruki Sato1, Koichiro Miyanishi2,3, Makoto Negoro3,4, Akinori Kagawa2,3, Yusuke Nishiyama5,6, Koichi
Nakamura7, Munehiro Inukai7
1 Graduate School of Sciences and Technology for Innovation, University of Tokushima
2 Graduate School of Engineering Science, University of Osaka
3 Center for Quantum Information and Quantum Biology, University of Osaka
4 Institute for Quantum Life Science, National Institutes for Quantum Science and Technology
5 RIKEN - JEOL Collaboration Center
6 JEOL RESONANCE Inc.
7 Graduate School of Technology, Industrial and Social Sciences, University of Tokushima

Dynamic nuclear polarization using photo-excited electron spin (Triplet DNP) can significantly improve
the sensitivity of NMR measurements at room temperature. This hyperpolarization technique has been
applied to several small molecules such as, metal-organic framework, drug molecules, and biomolecules.
Here, we present Triplet-DNP of eutectic crystals methods to hyperpolarize metabolic biomolecules. We have
performed powder X-ray diffraction measurement to confirm the crystal structure of the eutectic crystals andUV-vis spectroscopy to investigate in which region pentacene was doped. Furthermore, the spin diffusion
coefficient of 1H were investigated from two dimensional 1H-1H exchange NMR experiments and comparison
among the relaxation time of the eutectic polycrystals, benzoic acid polycrystals, and polycrystals of thetarget molecules. These results conclude that the eutectic crystals have small domain where polarization
diffuse from benzoic acid to target analyte until the relaxation time.
ᗎㄽ][ᗎ᰾ ࢫ ࣆ ࣥࡢ ೫ ᴟ ⋡ ࢆ ྥ ୖ ࡉࡏ ࡿᡭ ẁ ࡢ୍ ࡘ࡟ ග ບ㉳ ୕ 㔜 㡯≧ ែ ࡢ 㟁Ꮚ ࢫࣆ ࣥ ࢆ ⏝࠸ࡓ
DNP(Triplet DNP : Triplet dynamic nuclear polarization)ࡀᣲࡆࡽࢀࡿࠋග↷ᑕ࡛⏕ࡌࡿ㧗࠸㟁Ꮚࢫࣆࣥ೫ᴟࢆ೫ᴟ※࡜ࡋ࡚⏝࠸ࡿࡇ࡜࡛ࠊᐮ๣ࢆ⏝࠸ࡎᐊ ࡛NMR ᐃឤᗘࢆ኱ᖜ࡟ྥୖࡉࡏࡿࡇ࡜
ືⓗ᰾೫ᴟ㸪MAS NMR㸪ඹᬗ‫ࡁࡿࡣ࠺࡜ࡉۑ‬㸪ࡳࡸ࡟ࡋࡇ࠺࠸ࡕࢁ࠺㸪ࡡࡈࢁࡲࡇ࡜㸪࠿ࡀࢃ࠶ࡁࡢࡾ㸪࡟ࡋࡸࡲࡺ࠺ࡍࡅ㸪࡞࠿ࡴࡽࡇ࠺࠸ࡕ㸪࠸ࡠ࠿࠸ࡴࡡࡦࢁ

－ 310 －

ࡀ࡛ࡁࡿ[1]ࠋࡋ࠿ࡋࠊ೫ᴟ※࡛࠶ࡿ࣌ࣥࢱࢭࣥࡀ㞴⁐ࡢࡓࡵࠊ⏕యศᏊ୰࡬ࡢศᩓࡀᅔ㞴࡛࠶ࡗࡓࠋ
ࡇࢀࡲ࡛࡟ࠊྍ⁐ᛶ೫ᴟ※ࡢ฼⏝[2]ࡸ⁐ゎDNP࡜NOE(Nuclear Overhauser Effect)ࢆ⤌ࡳྜࢃࡏࡓప
ศᏊ೫ᴟࡢሗ࿌౛[3]࡞࡝ࡀ࠶ࡿࡀࠊ೫ᴟ⋡ࡸᐇ㦂 ᗘ࡞࡝࡟ㄢ㢟ࡀṧࡉࢀ࡚࠾ࡾࠊᐊ ࡛㧗࠸೫ᴟ⋡ࢆྍ⬟࡜ࡍࡿᡭἲࡢ㛤Ⓨࡀồࡵࡽࢀ࡚࠸ࡿࠋ
ᮏ◊✲࡛ࡣࠊඹᬗἲࢆ⏝࠸ࡓTriplet DNP࡟ὀ┠ࡋࠊࡑࡢᵓ㐀ࡸ೫ᴟᣑᩓ㐣⛬ࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜
࡟ຍ࠼ࠊ㐺⏝⠊ᅖࡢᣑᙇࢆ⾜ࡗࡓࠋඹᬗ࡜ࡣࠊ㸰ࡘࡢపศᏊࢆྜᡂࡋࡓ㝿࡟࠾஫࠸ࡢ⤖ᬗ┦ࡀ⥔ᣢࡋࡓ≧ែ࡛ΰࡊࡾྜ࠺⤖ᬗࡢࡇ࡜࡛࠶ࡿࠋࡇࢀࡲ࡛࡟ࠊ೫ᴟ※࡛࠶ࡿ࣌ࣥࢱࢭࣥࢆศᩓࡋࡓᏳ
ᜥ㤶㓟࡜ࢱ࣮ࢤࢵࢺ࡜࡞ࡿศᏊࢆΰྜࡉࡏඹᬗ࡜ࡍࡿࡇ࡜࡛ࢱ࣮ࢤࢵࢺศᏊࡢ㉸೫ᴟ໬ࡀྍ⬟࡜࡞ࡗ࡚࠸ࡿ[4]ࠋඹᬗἲࡣᵝࠎ࡞ศᏊ࡟㐺⏝࡛ࡁࡿᑗ᮶ᛶࡀ࠶ࡿࡀࠊሗ࿌౛࡛ࡣࠊᏳᜥ㤶㓟(࣌ࣥࢱࢭࣥࢆศᩓࡋࡓ)࡜Ᏻᜥ㤶㓟㢮ఝ໬ྜ≀(ࢱ࣮ࢤࢵࢺศᏊ)࠿ࡽ⤌ࡳୖࡀࡿඹᬗࡢ฿㐩೫ᴟ⋡ࡢሗ࿌ࡢࡳ࡟࡜࡝ࡲࡗࡓࠋඹᬗἲࢆᗈࡃᛂ⏝ࡍࡿࡓࡵ࡟ࡣࠊ࢝ࣝ࣎ࣥ㓟ࡸⰾ㤶᪘ࢆྵࡲ࡞࠸ศᏊࢆࢱ࣮
ࢤࢵࢺศᏊ࡜ࡋ࡚ࠊ㧗೫ᴟ໬ࡍࡿࡇ࡜ࡸࡑࡢᵓ㐀ࡸ೫ᴟᣑᩓ㐣⛬ࡢ⪃ᐹࢆ⾜࠺ࡇ࡜ࡀ୙ྍḞ࡛࠶ࡿࠋࡑࡇ࡛ࢡ࢚ࣥ㓟ᅇ㊰ࡢ୍㒊࡛࠶ࡿࢥࣁࢡ㓟ࠊ⢾࡛࠶ࡿ࢚ࣜࢫࣜࢺ࣮ࣝࡸ⸆࡛࠶ࡿ࢝ࣇ࢙࢖ࣥ
࡞࡝ࡢ⏕యศᏊࢆࢱ࣮ࢤࢵࢺศᏊ࡜ࡋࠊᏳᜥ㤶㓟࡜ࡢඹᬗࢆྜᡂࡋࠊTriplet DNP࡟ࡼࡾ㧗೫ᴟ໬࡟ᡂຌࡋࡓࠋࡲࡓࠊඹᬗࡢᵓ㐀ゎᯒࡸ೫ᴟᣑᩓ㐣⛬ࢆᅛయ㧗ศゎ⬟NMR࡟ࡼࡗ࡚᫂ࡽ࠿࡟ࡋࡓࠋ
[ඹඹᬗࡢྜᡂ࡜ᵓ㐀]Ᏻᜥ㤶㓟࡟ᑐࡋࠊ࣌ࣥࢱࢭࣥ(0.06 mol%)ࢆῧຍࡋࠊຍ⇕⼥ゎ(200ႏ)ྜᡂ࡟ࡼࡾ࣌ࣥࢱࢭࣥࢆᏳ
ᜥ㤶㓟⤖ᬗ┦୰࡟ศᩓࡉࡏࡓ(௨ୗᏳᜥ㤶㓟ࢆ BAࠊ࣌ࣥࢱࢭࣥࢆศᩓࡋࡓᏳᜥ㤶㓟ࢆ BAP ࡜࿧ࡪ)ࠋᚓࡽࢀࡓ BAP ࡜ࢱ࣮ࢤࢵࢺศᏊ࡛࠶ࡿࢥࣁࢡ㓟ࠊ࢚ࣜࢫࣜࢺ࣮ࣝࠊ࢝ࣇ࢙࢖ࣥࢆ໬Ꮫ㔞ㄽẚ 1 : 1 ࡛ຍ⇕⼥ゎ(200ႏ)ྜᡂ࡟ࡼࡾඹᬗࢆྜᡂࡋࡓ(௨ୗࢥࣁࢡ㓟ࢆ SUAࠊ࢚ࣜࢫࣜࢺ࣮ࣝࢆ ETࠊ
࢝ࣇ࢙࢖ࣥࢆ CAF ࡜࿧ࡪ)ࠋ
 ⤖ᬗᵓ㐀ゎᯒࢆ⾜࠺ࡓࡵࠊྛࢧࣥࣉࣝࡢ⢊ᮎ XRD

ᐃࢆ⾜ࡗࡓࠋ࡝ࡢࢧࣥࣉࣝࡶ BA ࡢࢫ࣌ࢡࢺࣝ࡜ࢱ࣮ࢤࢵࢺศᏊ༢యࡢࢫ࣌ࢡࢺࣝࡢ㔜ࡡྜࢃࡏࡢࢫ࣌ࢡࢺࣝࡀ☜ㄆࡉࢀࡓࠋࡇࢀࡣ࠾஫࠸
ࡢ⤖ᬗᵓ㐀ࡀ⥔ᣢࡋࡓ≧ែ࡛⤖ᬗࢆᙧᡂࡋ࡚࠸ࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋඹᬗࡢ≉ᚩ࡛࠶ࡿࡑࢀࡒ
ࢀࡢ⤖ᬗ┦ࢆ⥔ᣢࡋࡓ≧ែ࡛ΰࡊࡗࡓ⤖ᬗ࡜୍⮴ࡋ࡚࠾ࡾࠊBA ࡜ SUAࠊETࠊCAF ࡣඹᬗࢆᙧᡂ
ࡋ࡚࠸ࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓࠋ

Fig. 1. PXRD of (a) BA-CAF, (b) BA-ET and (c) BA-SUA in eutectics.
ඹᬗ࡟࠾ࡅࡿ࣌ࣥࢱࢭࣥࡢ఩⨨][ඹ೫ᴟ※࡛࠶ࡿ࣌ࣥࢱࢭࣥࡢ఩⨨ࢆ᫂ࡽ࠿࡟ࡍࡿࡓࡵࠊ3ࡘࡢඹᬗ࡜BAPࡢUV-vis ᐃࢆ⾜ࡗࡓࠋ3ࡘࡢඹᬗ࡜BAPࡣඹ࡟࣌ࣥࢱࢭࣥ⏤᮶ࡢග྾཰ࣆ࣮ࢡࢆ♧ࡋࠊ࣌ࣥࢱࢭࣥࡀඹᬗ࠾ࡼࡧBA୰࡟
ศᩓࡋ࡚࠸ࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋຍ࠼࡚ࠊග྾཰ࣆ࣮ࢡࡀ඲୍࡚⮴ࡋࡓࡇ࡜࠿ࡽࠊ࣌ࣥࢱࢭࣥ࿘㎶ࡢ⎔ቃࡣྠࡌࠊࡍ࡞ࢃࡕඹᬗ୰࡛ࡢ࣌ࣥࢱࢭࣥࡣBAࡢ⤖ᬗ┦୰࡟ศᩓࡋ࡚࠸ࡿࡇ࡜ࡀண᝿ࡉࢀࡿࠋ

－ 311 －

[ඹඹᬗࡢ Triplet DNP]ࡇࢀࡽ㸱ࡘࡢඹᬗ࡟ᑐࡋ
࡚ࠊTriplet DNP ࢆ⾜ࡗࡓࠋࢱ࣮ࢤࢵࢺศᏊࡢ೫ᴟࡀ᫂☜࡟࡞ࡿࡼ࠺࡟ࠊᏳᜥ㤶㓟ࡢ඲࡚ࡢỈ⣲ࠊཬࡧࢱ࣮ࢤࢵࢺศᏊ
ࡢỈ㓟ᇶ࡜࢝ࣝ࣎࢟ࢩࣝᇶࡢ
Ỉ⣲ࢆ㔜Ỉ⣲࡜஺᥮ࡋࡓヨᩱ(d6-BA : D ໬⋡ 92%ࠊd4-ET : D
໬⋡ 60%ࠊ
d2-SUA : D ໬⋡ 95%)ࢆ⏝࠸ࡓࠋTriplet DNP ࢆ⾜ࡗࡓᚋࡢ¹H NMRᐃ࡟࠾࠸࡚ࠊ

᫂ࡽ࠿࡞ቑᙉࡉࢀࡓಙྕࢆ☜ㄆ࡛ࡁࡓ(Fig. 2 (b)㯮Ⰽ)ࠋࡇࡢ
⤖ᯝ࠿ࡽࠊ࡝ࡢඹᬗࡶ 0.4 T ࡢ⇕ᖹ⾮≧ែ࡟ẚ࡭ࠊ100 ಸ௨ୖࡢ೫ᴟ⋡ࢆ♧ࡋ(Fig. 2 (c)) ࠊᐊ

Fig. 2. Triplet DNP of (a) molecular with eutectic and (b) 1H NMRୗ࡛⏕యศᏊࡢ㧗೫ᴟ໬࡟

spectra (black) and thermal 1H NMR spectra (gray). (c) The buildup

ᡂຌࡋࡓࠋ

curve of target molecular in eutectics.

೫ᴟᣑᩓ㐣⛬ࡢゎ᫂][೫ḟ࡟ࠊ࡝ࡢࡼ࠺࡟࣌ࣥࢱࢭࣥࢆྵࡴᏳᜥ㤶㓟ࡢ೫ᴟ┦࠿ࡽࢱ࣮ࢤࢵࢺศᏊࡢ⤖ᬗ┦࡟೫ᴟࡀ⛣ືࡋ࡚࠸ࡿ࠿ࢆㄪ࡭ࡓࠋ㒊ศⓗ࡞㔜Ỉ⣲໬ࢆࡋࡓ d5-BA(࣋ࣥࢮࣥ⎔ࢆ㔜Ỉ⣲໬)࡜ࢱ࣮ࢤࢵࢺศ
Ꮚ࠿ࡽ࡞ࡿඹᬗࢆྜᡂࡋࠊ1H MAS NMR ࡟ࡼࡾ T1

ᐃࢆ⾜ࡗࡓࠋ☢ሙᙉᗘࡣ 14 Tࠊヨᩱᅇ㌿㏿

ᗘࡣ 70 kHz ࡛࠶ࡿࠋd5-BA ࡢ࢝ࣝ࣎ࣥ㓟ࡢ T1 ࡣࠊd5-BA-ET ࡛ࡣ 61.2 s ࠿ࡽ 55.4 sࠊd5-BA-CAF ࡛ࡣ 29.9 s ࡟ῶᑡࡋࡓࠋET ࡢ࢚ࢳࣞࣥ࡜ CAF ࡢ࣓ࢳࣝࡢ T1 ࡶ d5-BA-ET ࡜ d5-BA-CAF ࡛ࡑࢀࡒࢀ 573 s ࠿ࡽ 52.3 sࠊ
33.3 s ࠿ࡽ 28.3 s ࡟ῶᑡࡋ࡚࠾ࡾࠊd5-BA ࡢ࢝ࣝ࣎ࣥ㓟࡜ࢱ࣮ࢤࢵࢺศᏊࡢ࢚ࢳࣞࣥࠊ࣓ࢳࣝࡢ T1ࡣඹ᭷ࡋ࡚࠸ࡿࡇ࡜ࡀ☜ㄆࡉࢀࡓࠋ㉸㧗㏿ MAS NMR ᮲௳ୗ࡛ࡣࠊ1H-1H ཮ᴟᏊ࢝ࢵࣉࣜࣥࢢࡀ
ᢚไࡉࢀࡿࡓࡵࠊࢫࣆࣥᣑ
ᩓࡀ㐜ࡃ࡞ࡿࠋࡇࢀࡽࡢ T1
ゎᯒࡣࠊࢫࣆࣥᣑᩓࡀ㐜࠸≧ែ࡛ࡶඹᬗ୰ࡢ☢໬ࡀᆒ୍࡟ࢫࣆࣥᣑᩓࡋ࡚࠸ࡿࡇ
࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋඹᬗ୰
࡟࠾࠸࡚ࠊ⦆࿴᫬㛫ࡢ㛫ࡣ೫ᴟ┦(BAP)࠿ࡽࢱ࣮ࢤࢵ
ࢺศᏊࡢ⤖ᬗ┦࡬☢໬ࡀᣑᩓྍ⬟࡜࠸࠺ࡇ࡜ࡀ᫂ࡽ࠿
࡜࡞ࡗࡓࠋ

Fig. 3. T1 saturation recovery of (a) d5-BA-ET, (b) d5-BA-CAF.

－ 312 －

ḟ࡟ࠊ¹H 2D exchange MAS NMR

ᐃࢆ d5-BA ࡜ CAF ࡟ࡼࡿඹᬗ࡟ᑐࡋ࡚⾜ࡗࡓࠋ஺᥮᫬㛫(mixing time)ࡀ 0.1 s ࡢࢫ࣌ࢡࢺࣝࡣ CAF ⤖ᬗ┦ෆࡢ☢໬஺᥮ࢆ♧ࡍࣆ࣮ࢡࡢࡳ♧ࡋࡓ(Fig. 4 (a))ࡀࠊ10 s ࡢࢫ࣌ࢡࢺ࡛ࣝ
ࡣ d5-BA ࡢ࢝ࣝ࣎ࣥ㓟࡜
CAF ࡢ࣓ࢳࣝ㛫࡛☢໬஺᥮ࢆ♧ࡍࢡࣟࢫࣆ࣮
ࢡࢆ☜ㄆ࡛ࡁࡓ (Fig. 4(b)) ࠋ ࡇ ࢀ ࡣ d5-BA ࡜
CAF ࡀ⦆࿴᫬㛫ෆ࡛ࢫࣆࣥᣑᩓࡀྍ⬟࡞㊥㞳࡟㏆᥋ࡋ࡚࠸ࡿࡇ࡜ࢆ
♧ࡋ࡚࠾ࡾࠊࡍࢃ࡞ࡕࠊ
BAP ࡟ ࡼ ࡿ ㉸ ೫ ᴟ ࡀ
CAF ࡟ᣑᩓࡋ࡚࠸ࡿࡇ

Fig. 4. 2D exchange 1H MAS NMR spectra of d5-BA-CAF mixing time of(a) 0.1 s and (b) 10 s.

࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋࡲ࡜ࡵ][ࡲ ᮏ◊✲࡛ࡣࠊ࣌ࣥࢱࢭࣥࢆศᩓࡉ
ࡏࡓᏳᜥ㤶㓟࡜ࢥࣁࢡ㓟ࠊ࢚ࣜࢫࣜ
ࢺ࣮ࣝࡸ࢝ࣇ࢙࢖ࣥࡢඹᬗࢆྜᡂࡋ
ࡓࠋUV-visᐃ࡟ࡼࡾࠊඹᬗ࡟࠾ࡅ

ࡿ೫ᴟ※ࡢ࣌ࣥࢱࢭࣥࡀࢱ࣮ࢤࢵࢺ
ศᏊࡢ⤖ᬗ┦࡛ࡣ࡞ࡃࠊᏳᜥ㤶㓟ࡢ⤖ᬗ┦୰࡟ศᩓࡉࢀ࡚࠸ࡿ࡜ண᝿ࡋ
ࡓࠋࡇࢀࡽඹᬗࢆ Triplet DNP ࡟ࡼࡾࠊᐊ࡛㧗೫ᴟ໬ࡍࡿࡇ࡜࡟ᡂຌࡋ

ࡓࠋ2D exchange ¹H MAS NMR ࢫ࣌ࢡࢺࣝ࡟ࡼࡾࠊᏳᜥ㤶㓟࡜ࢱ࣮ࢤࢵࢺ
ศᏊ㛫࡛ࢫࣆࣥᣑᩓࡀ☜ㄆ࡛ࡁࡓࠋ
ࡇࡢࡇ࡜࠿ࡽࠊඹᬗࢆ⏝࠸ࡓ Triplet
DNP ࡛ࡣࠊᏳᜥ㤶㓟ࡢ೫ᴟ┦࠿ࡽࠊࢫࣆࣥᣑᩓ࡟ࡼࡾࢱ࣮ࢤࢵࢺศᏊࡢ
⤖ᬗ┦࡬೫ᴟࡀ⛣ືࡍࡿࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿ(Fig. 5)ࠋ

Fig. 5. (a) Synthesis of eutectic and (b) eutectic matrix andTriplet DNP. (c, d) Spin diffusion of polarization from thepolarization phase with polarization source to target phase.

[Reference][1] K. Tateishi, M. Negoro, et al., Proc. Natl. Acad. Sci. U.S.A. 2014, 111, 7527.
[2] N. Yanai, et al., J.Phys. Chem. Lett. 2021, 12, 2645.
[3] T. R. Eichhorn, A. J. Parker, I. Schwartz, et al., J. Am. Chem. Soc. 2022, 144, 2511.
[4] A. Kagawa, et al., J.Phys. Chem. A. 2018, 122, 9670.

－ 313 －

P81

ぶỈᛶࢼࣀ⣽Ꮝ࡟㛢ࡌ㎸ࡵࡽࢀࡓ㝵ᒙⓗ࡞ỈศᏊࢡࣛࢫࢱ࣮ࡢ
2H-NMRࢫ࣌ࢡࢺࣝゎᯒ‫ۑ‬㰺⸨ ᫂, ᑿⰼ㥴୍, ୪ᮌᬛဢ, ᑠᯘᩥஓ, ᰩཎᣅஓ2, Ỉ㔝ඖ༤2,⏣ᡤ ㄔ
1 ᮾி⌮⛉኱Ꮫ࣭⌮Ꮫ㒊➨㸯㒊໬Ꮫ⛉
2 㔠ἑ኱Ꮫ࣭⌮ᕤ◊✲ᇦ

2H-NMR Spectroscopy on Hierarchical Water Molecule Clusters Confined to Hydrophilic

Nanoporous Channels‫ۑ‬Akira Saito1, Shunichi Obana1, Tomoya Namiki1, Fumiya Kobayashi1, Takuya Kurihara2, Motohiro
Mizuno2, Makoto Tadokoro1
1

Department of Chemistry, Faculty of Science, Tokyo University of Science

2 Graduate School of Natural Science and Technology, Kanazawa University

We have investigated on water molecular clusters (WMCs) confined to hydrophilic quasi-1-D nanoporous channels in the self-organized molecular crystal. The WMC structure has a hierarchical structure ofthree phases, which is different by the strength of H-bonding interaction. This time, by 2H-NMR spectra,
three kinds of WMC layers would be observed in the melting and freezing state. It was confirmed that, by
X-ray crystal analysis, the crystal structures of a dynamic WMC in the melting state and a static WMC in
the freezing one were clarified to have three hierarchical layer structures.
࠙ㅖゝࠚ‽୍ḟඖࢼࣀ⣽Ꮝࢆ᭷ࡍࡿぶỈᛶศᏊ⤖ᬗࡢ(a) 㼍 㼙 㼛 㼞 㼜 㼔 㼛 㼡 㼟 㼣 㼍 㼘㼘ෆ 㒊 ࡟ 㛢 ࡌ ㎸ ࡵ ࡽ ࢀ ࡓ Ỉ ศ Ꮚ ࢡ ࣛ ࢫ ࢱ ࣮ (Water
molecular~1.6 nmcluster:

WMC) ࡣ, እቨ࡟Ꮡᅾࡍࡿ࿘ᮇⓗ࡞ぶỈᛶᐁ⬟ᇶࡢᙳ㡪࡛ప࡛ࡣእഃ࠿ࡽị⤖(b)㼏 㼞 㼥 㼟 㼠㼍 㼘㼘㼕㼚 㼑 1.6
㼣 㼍~1.8
㼘㼘 nmindiametercrystalline phase

amorphous phasecrystalline
Hater
2O
Crystalline W

bulk Ice
ice Ichierarchical
Hierarchicalstructure
Structure

Crystalline Water

crystalline H2O
amorphous phasecrystalline phase
Hardly freezingwater
hard-to-freeze
H2O

Non-freezingwater
non-freezed
H2O

Fig.1. Images of freezing behaviours of WMC{[M (H2bim)3](TMA)·20H2O}n(a) Mesoporous
silica and (b) Nano-porous
molecular crystal
Mesoporous Silica

ࡋ, WMCෆ㒊࡟࠸ࡃIII

Nano-porous Single Crystal

Chem. Select, 4, 6627 (2019)࡟ࡘࢀ࡚෾⤖ࡋ࡟ࡃࡃ࡞ࡿ. ࡇࢀࡣእቨࡀ –Si–O–Si– ᇶࡢ࢔ࣔࣝࣇb࢓ࢫ࠿ࡽ࡞ࡿMCM-41࡞࡝ࡢ࣓ࢯ
࣏࣮ࣛࢫᮦᩱࡀ, ෆ㒊࠿ࡽࣂࣝࢡ
oaFig. 2. Crystal structure of 1.

ࡢ Ic ࡟ị⤖ࡋ, እቨ௜㏆ࡢ H2O ࡣᵓ㐀ࢆࡶࡓࡎ࡟෾⤖ࡍࡿഴྥ࡜ࡣ␗࡞ࡗ࡚࠸ࡿ. ࡑࡢࡓࡵ㸪ぶỈᛶࢼࣀከᏍ㉁⤖ᬗෆ࡟ᤕࡽ
࠼ࡽࢀࡓWMCࡣࣂࣝࢡị࡜␗࡞ࡗࡓᣲືࢆ♧ࡋ, ౛࠼ࡤWMC

ࡢ෾⤖ᵓ㐀ࡣࣂࣝࢡị࡜␗࡞ࡗࡓᵓ㐀ࢆ♧ࡍ. (Fig.1) ᮏ◊✲࡛ࡣ, ぶỈᛶศᏊከᏍ㉁⤖ᬗෆ࡟㛢ࡌ㎸ࡵࡽࢀࡓWMCࡢᛶ㉁ࢆᅛయ 2H-NMR ࡛ㄪᰝࡍࡿࡇ࡜ࢆ┠ⓗ࡟࠶ࡆࡓࠋ
ᅛయ 2H-NMR, ศᏊᛶࢼࣀከᏍ㉁⤖ᬗ, ỈศᏊࢡࣛࢫࢱ࣮
‫ࡽࡁ࠶࠺࡜࠸ࡉۑ‬㸪࠾ࡤ࡞ࡋࡹࢇ࠸ࡕ㸪࡞ࡳࡁ࡜ࡶࡸ㸪ࡇࡤࡸࡋࡩࡳࡸ㸪ࡃࡾࡣࡽࡓࡃࡸ㸪ࡳࡎࡢࡶ࡜ࡦࢁ, ࡓ࡝ࡇࢁࡲࡇ࡜

－ 314 －

⚾ࡓࡕࡢ◊✲ᐊ࡛ࡣ‽୍ḟඖࢼࣀࢳࣕࢿࣝᵓ㐀࡟WMCࢆ㛢ࡌ㎸ࡵࡓᵓ㐀ࢆࡶࡘ{[CoIII(H2bim)3](TMA)·20H2O}n (1) (H2bim = 2,2'-biimidazole, TMA3– = trimesate㸧ࡢ⤖ᬗྜᡂ࡟ᡂຌࡋࡓ. (M = CoIII,
RhIII, RuIII,CrIII, OsIII ࡀ▱ࡽࢀ࡚࠸ࡿ.) ᅛయࡢ2H-NMRࡢ ᐃ࡟⤖ᬗ 1 ࢆ㑅ᢥࡋࡓ⌮⏤ࡣ CoIII㘒యࡀᐃ࡟㐺ࡋࡓLS (low spin) ࡢ཯☢ᛶࡔ࠿ࡽ࡛࠶ࡿ㸬Fig. 2 ࡟♧ࡋࡓࡼ࠺࡟, つ๎ᛶࡢ㧗࠸‽୍ḟඖぶỈᛶࢼࣀࢳࣕࢿࣝ (ȭ~1.6 nm) ࢆ᭷ࡍࡿከᏍ㉁⤖ᬗ࡟⮬ᕫ⤌⧊໬ࡍࡿ㸬ࡇࡢෆ㒊࡟ྲྀࡾ㎸ࡲ
ࢀࡓWMCࡣ㸪⣽Ꮝቨ㠃࡟࠶ࡿ –COO– ᇶࡢぶỈᛶOཎᏊ࡜ࡢỈ⣲⤖ྜ࡛ᵓ㐀໬ࡉࢀ࡚࠸ࡓ㸬ࡑࡋ࡚㸪ࡑࡢ┦㌿⛣๓ᚋ࡛ࡢWMCᵓ㐀ࢆồࡵࡿࡇ࡜࡟ᡂຌࡋࡓ.[1] X⥺ᵓ㐀ゎᯒ࡛ࡣ࿘㎶ࡢỈ⣲⤖ྜࡢ≧ែ࡟ࡼࡗ࡚㸪⼥ゎ≧ែࡸ෾⤖≧ែ࡛ࡶWMCࡢᵓ㐀ࡣ 3 ᒙࡢᵓ㐀ࢆࡶࡘࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗ࡚
࠸ࡿ. ᅛయࡢ2H-NMRࡢ ᐃ࡟ࡼࡗ࡚㸪H2O ྠኈࡢỈ⣲⤖ྜᛶ┦஫స⏝ࡢ㐪࠸࠿ࡽ㸪WMCࡢ3ᒙ࠿ࡽ࡞ࡿ㝵ᒙᵓ㐀ࢆほ ࡍࡿࡇ࡜ࢆヨࡳࡓ㸬࠙ᐇ㦂ࠚ[CoIII(H2bim)3](NO3)3 ࡜ K3TMA ࢆỈ୰࡛ࡺࡗࡃࡾ࡜ᣑᩓࡉࡏࡿࡇ࡜࡛㸪㉥Ⰽࡢභゅᰕ≧⤖ᬗ࡜ࡋ࡚ 1 ࢆᚓࡓ㸬ࡇࢀࢆD2O (99.9%) ࡟㸯᫬㛫⛬ₕࡅ㎸ࡴ᧯సࢆ㸰ᅇ⾜࠸㸪ෆ㒊࡟ྲྀࡾ㎸ࡲࢀࡓ H2O ࢆ D2O ࡟⨨᥮ࡋࡓ {[CoIII(D2bim)3](TMA)·20D2O}n (2)ࢆᚓࡓ㸬2 ࢆ◳㉁࢞ࣛࢫ〇ࢧࣥࣉࣝ⟶ (ȭ4 mm) ࡟ 20 mg ⛬ᗘධࢀ㸪
ᾮయN2࡟ₕࡅ࡚⤖ᬗෆ㒊ࡢD2Oࢆ෾⤖ࡉࡏࡓ㸬ࡇࡢ࢞ࣛࢫ⟶ෆࢆ┿✵࣏ࣥࣉ࡛⬺Ẽࡋ㸪↝ࡁษࡿࡇ࡜࡛NMR ᐃࡢᚤ⤖ᬗ⢊ᮎࢧࣥࣉࣝ࡜ࡋ
ࡓ㸬ࡲࡓࠊ࢞ࣛࢫ⟶࡟ᩘ mm ࡟ᡂ㛗ࡋࡓ 2 ࡢ༢⤖ᬗ࡜D2O࡛‵ࡽࡏࡓ⥥ࢆᑒධࡋࡓ༢⤖ᬗࢧࣥࣉࣝࡶసᡂࡋࡓ㸬ࡇࢀࡽࡢࢧࣥࣉࣝࢆ
Bruker♫ࡢ400 MHz NMRࡢ⿦⨨ࢆ⏝࠸࡚, ᅄᴟᏊ࢚ࢥ࣮ἲ (ඹ㬆࿘Ἴᩘ61.44 MHz) ࡟ࡼࡾࡢᅛయ2H-NMRࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓ. ࡲࡓ, ᅛ
య2H-2ḟඖ஺᥮NMRࡶヨࡳ࡚࠸ࡿ࡜ࡇࢁ࡛࠶ࡿ㸬࠙⤖ᯝ࡜⪃ᐹࠚ Fig. 3 ࡟ 163 K ࠿ࡽ 243 K ࡲ࡛ࡢ 2 ࡢ⢊ᮎࢧࣥࣉࣝ
࡟ࡼࡿ2H-NMRࢫ࣌ࢡࢺࣝࡢ⤖ᯝࢆ♧ࡋࡓ㸬213 K࠿ࡽࣈ࣮ࣟࢻ࡞ࣆ࣮
ࢡ (–100 kHz ~ +100 KHz) ࡀඛ㗦໬ (–5 kHz ~ +5KHz) ࡋ࡚࠸ࡿࡇ࡜ࡀほࡉࢀࡓ㸬ࡇࡢ ᗘ௜㏆࡛⼥ゎจᅛࡢ┦㌿⛣ࡀ㉳ࡇࡗ࡚࠸ࡿࡶࡢ࡜⪃࠼࡚࠸ࡿ㸬ඛ㗦໬ࡋࡓࣆ࣮ࢡ࡟ࡶ␗᪉ᛶࡀ࠶ࡾ㸪WMCࡢࣆ࣮ࢡ࡛࠶ࡿ
ࡇ࡜ࡀศ࠿ࡿ㸬163 K࡟ࡣ࠸ࡃࡘ࠿ࢩࣙࣝࢲ࣮ࡀほ ࡉࢀࡿࡓࡵ㸪ᅄᴟᏊ⤖ྜᐃᩘ CQ ࡜㠀ᑐ⛠ᛶࣃ࣓࣮ࣛࢱ࣮Ȟࢆ⏝࠸࡚ࣇ࢕ࢵࢸ࢕ࣥࢢࢆ⾜ࡗࡓ㸬୰ᚰࡢࣈ࣮ࣟࢻ࡞ࣆ࣮ࢡ࡟ຍ࠼࡚㸪CQ ࡀ኱ࡁ࡞␗᪉ᛶࢆࡶࡘ
ࣆ࣮ࢡ(CQ = 219 kHz,Ȟ= 0.10) ࡜㸪ࡸࡸ␗᪉ᛶࡀᑠࡉ࡞ࣆ࣮ࢡ(CQ = 141 kHz, Ȟ

Fig. 3. Temperaturedepending solid-state= 0.20)ࡢ㸱ࡘ࡟ศゎ࡛ࡁࡿࡇ࡜ࡀศ࠿ࡗࡓ㸬ࡇࢀࡽࡢ3✀㢮ࡢࣆ࣮
ࢡࡣࠊWMCࡢ෾⤖ᵓ㐀ࡢ㐠ື࡟㉳ᅉࡋ࡚࠸ࡿࡶࡢ࡜⪃࠼࡚࠸ࡿ㸬
Fig. 4. Deconvolution of
2H-NMR of 2 at 163 K

pake dublet ࡟㏆࠸CQ = 219 kHzࡢࣆ࣮ࢡࢆ㝖࠸࡚㸪163 Kࡢ෾⤖ᵓ㐀࡛ࡶ2✀㢮ࡢD2Oࡢ㐠ື࣮ࣔࢻࢆṧࡋ࡚࠸ࡿࡶࡢ࡜⪃࠼࡚࠸ࡿ㸬ࡇࢀࡽࡢ㐠ື࣮ࣔࢻࡀWMCࡢ෾⤖ᵓ㐀࡜㛵ಀ࡙ࡅࡽࢀࡿ࠿᳨ウ୰࡛࠶ࡿ㸬ࡉࡽ࡟㸪༢⤖ᬗ 2 ࢆ⏝࠸࡚⼥ゎࡋࡓ ᗘ㡿ᇦ࡛ࢲ࢖ࢼ࣑ࢵࢡ࡞WMCࡢ㝵ᒙⓗ࡞ࢡࣛࢫࢱ࣮ᵓ㐀ࢆ☜ㄆ࡛ࡁࡿ࠿࡟ࡘ࠸࡚ࡶ᳨ウ୰࡛࠶ࡿ㸬

References[1] M. Tadokoro et al., Chem. Commun., 2006, 1274-1276[2] M. Tadokoro et al.,Chem. Lett., 2010,39, 186-187－ 315 －

P82Y

ከᏍᛶ㓄఩㧗ศᏊ࡟࠾ࡅࡿ஧㓟໬Ⅳ⣲࡜Ỉࡢືⓗᣲື࡜➇த྾╔‫ۑ‬㔠Ꮚ᐀ᖹࠊᰩཎᣅஓࠊỈ㔝ඖ༤ࠊ୰ᮧᾈ୍ࠊ≟㣫᐀ᘯ
1ᚨᓥ኱Ꮫ኱Ꮫ㝔๰ᡂ⛉Ꮫ◊✲⛉⌮ᕤᑓᨷ2㔠ἑ኱Ꮫ⌮ᕤ◊✲ᇦ≀㉁໬Ꮫ⣔3㔠ἑ኱Ꮫࢼࣀ࣐ࢸࣜ࢔ࣝ◊✲ᡤ

4ᚨᓥ኱Ꮫ኱Ꮫ㝔♫఍⏘ᴗ⌮ᕤᏛ◊✲㒊⌮ᕤᏛᇦ

Dynamics and competitive adsorption of carbon dioxide and water on PCP‫ۑ‬Sohei Kaneko1, Takuya Kurihara2, Motohiro Mizuno3, Koichi Nakamura4, Munehiro Inukai4
1

Graduate School of Sciences and Technology for Innovation, University of Tokushima

2 Graduate School of Natural Science and Technology, Kanazawa University
3

Nanomaterials Research Institute, Kanazawa University

4 Graduate School of Technology, Industrial and Social Sciences, Tokushima University

Separation and recovery of CO2 from exhaust gases is an important issue in modern society. Recently,
PCP has attracted much attention, and studies on CO2 separation and storage under wet conditions havebeen conducted. However, detailed analysis of CO2 adsorption sites, dynamics, and diffusion behavior
inside PCP under wet conditions is limited, and such information have been on demand to consider its
separation and storage capacity.
In this study, we focused on UTSA-16, which has high CO2 adsorption ability under wet conditions, andanalyzed the dynamics of CO2 and H2O with MAS NMR to elucidate the adsorption under wet conditions.
The NMR analyses shows specific dynamics of adsorbed H2O and competitive adsorption of CO2.
[ᗎㄽ]ᆅ⌫ ᬮ໬ࡢཎᅉ࡜࡞ࡿCO2ࡣⅆຊⓎ㟁ᡤࡸᕤሙࡢ᤼Ẽ࢞ࢫ࠿ࡽከ㔞࡟᤼ฟࡉࢀ࡚࠾ࡾࠊࡑࢀ
ࡽ᤼Ẽ࢞ࢫ࠿ࡽ஧㓟໬Ⅳ⣲ࢆศ㞳࣭ᅇ཰ࡍࡿᢏ⾡㛤Ⓨࡣ㔜せ࡞ㄢ㢟ࡢ୍ࡘ࡛࠶ࡿࠋ㏆ᖺࠊ‵₶⎔ቃୗ࡛ከ኱࡞࢚ࢿࣝࢠ࣮ࢆᚲせ࡜ࡏࡎ࡟CO2ศ㞳࣭㈓ⶶࢆྍ⬟࡜ࡍࡿᮦᩱ࡜ࡋ࡚ከᏍᛶ㓄఩㧗ศ
Ꮚ(PCP㸸Porous Coordination Polymer)ࡀὀ┠ࡉࢀ࡚࠸ࡿࠋPCPࡣ㔠ᒓ࢖࢜ࣥ࡜᭷ᶵ㓄఩Ꮚ࡛ᵓᡂࡉ
ࢀ࡚࠾ࡾࠊࡑࡢ⤌ࡳྜࢃࡏḟ➨࡛⣽Ꮝࡢ኱ࡁࡉࡸᙧ≧ࢆ⮬⏤࡟タィࡍࡿࡇ࡜ࡀฟ᮶ࡿ࣏࣮ࣛࢫᮦ
ᩱ࡛࠶ࡿ[1][2]ࠋ
୍⯡ⓗ࡟ࠊ‵₶⎔ቃୗࡢPCPࡣCO2ࡼࡾᴟᛶศᏊ࡛࠶ࡿH2Oࡀඃඛⓗ࡟྾╔ࡍࡿࡓࡵࠊ྾╔ࢧ
࢖ࢺࡀH2O࡟༨᭷ࡉࢀ࡚ࡋࡲ࠸ࠊCO2ࡢ྾╔㔞ࡀⴭࡋࡃῶࡿࠋ‵₶⎔ቃୗ࡛ࡶCO2྾╔㔞ࢆ⥔ᣢ࡛ࡁࡿPCPࡢሗ࿌౛ࡣࢃࡎ࠿࡟࠶ࡿࡀ [3]ࠊࡑࡢヲ⣽࡞ᶵᵓࡣ୙࡛᫂࠶ࡾࠊゎ᫂ࡀᮃࡲࢀࡿࠋࡇࢀ
ࡲ࡛PCPෆ㒊࡟࠾ࡅࡿCO2ศ㞳࣭྾╔ࡢ◊✲[4]ࡣ┒ࢇ࡟⾜ࢃࢀ࡚࠸ࡿࡀ஝⇱㞺ᅖẼୗ࡟㝈ࡽࢀ࡚࠾ࡾࠊ‵₶⎔ቃୗࡢPCPෆ㒊࡟࠾ࡅࡿH2OཬࡧCO2ࡢศᏊ㐠ືࡸᣑᩓᣲື࡞࡝࡟㛵ࡍࡿヲ⣽࡞ゎᯒ౛ࡣ࡯ࡰⓙ↓࡛࠶ࡿࠋ
MAS NMR‫ࢁࡦࡡࡴ࠸࠿ࡠ࠸ࠊࡕ࠸࠺ࡇࡽࡴ࠿࡞ࠊࢁࡦ࡜ࡶࡢࡎࡳࠊࡸࡃࡓࡽࡣࡾࡃࠊ࠸࡬࠺ࡑࡇࡡ࠿ۑ‬－ 316 －

ᮏ◊✲࡛ࡣࠊ‵₶⎔ቃୗ࡛㧗࠸CO2྾╔⬟ࢆ⥔ᣢࡍࡿUTSA-16 [K2Zn3(C6H4O7)2] [5] ࡟ὀ┠ࡋࠊ
MAS NMRゎᯒ࡟ࡼࡗ࡚PCPෆ㒊ࡢH2O࡜CO2ࡢ఩⨨ࡸ㐠ືࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜࡛ࠊ‵₶ΰྜ࢞ࢫ࡟࠾ࡅࡿCO2྾╔ᶵᵓࡢゎ᫂࡟ྲྀࡾ⤌ࢇࡔࠋ」ᩘ✀㢮ࡢ࢞ࢫࢆPCP࡜࡜ࡶ࡟ᑒධ࡛ࡁࡿMASヨᩱ⟶࡜ᑟධ⿦⨨ࢆ౑⏝ࡋࠊD2O࡜CO2ࡢΰྜ࢞ࢫࢆPCP࡟ᑒධࡋ࡞ࡀࡽࠊ‵ᗘ㞺ᅖẼୗ࡟࠾ࡅࡿCO2
࡜D2Oࠊ࠾ࡼࡧUTSA-16ࡢNMRゎᯒࢆ⾜ࡗࡓࠋ[ΰྜ࢞ࢫᑒධ⿦⨨]ᚑ᮶ࡢMAS⏝ࢧࣥࣉࣝ⟶࡛ࡣࢧࣥࣉࣝ
⟶ෆ࡟CO2ศᏊࢆᑒධࡍࡿࡇ࡜ࡣᅔ㞴࡛࠶ࡿࠋᮏ◊✲࡛ࡣJEOL〇4mmࢧࣥࣉࣝ⟶ࡢᙧ≧ࢆ࣮࣋ࢫ࡟タィࡉࢀࡓࢧࣥࣉࣝ
⟶ࢆ౑⏝ࡋࡓ(Fig1.(a))[6]ࠋOࣜࣥࢢࢆ2ಶ⿦╔ࡋࡓࢫࢡ࣮ࣜࣗ࢟ࣕࢵࣉ࡟ࡼࡾࠊヨᩱ✵㛫ࡢ࢞ࢫᅽࢆಖࡗࡓࡲࡲ࣮ࣟࢱ࣮ࢆ
ᐦ㛢ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋࢫࣆࢽࣥࢢ࢟ࣕࢵࣉࡣࠊJEOL〇4mmࢫࣆࢽࣥࢢ࢟ࣕࢵ
ࣉࢆ౑⏝ࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋ࢞ࢫᑒධࢳ
ࣕࣥࣂ࣮(Fig1.(b))ࢆ౑⏝ࡍࡿࡇ࡜࡛ᵝࠎ࡞ᅽຊࡢỈཬࡧ」ᩘ࢞ࢫࢆࢧࣥࣉࣝ⟶࡟ᑒධࡍࡿࡇ࡜ࡀྍ⬟࡛࠶ࡿࠋᮏ◊✲࡛ࡣ
D2O࡟ࡼࡾຍ‵ࡋࡓN2࢞ࢫ࡜13C CO2࢞ࢫ
ࢆ⏝࠸ࡓࠋFig 1. (a) 4mm ࢫࢡ࣮ࣜࣗࢧࣥࣉࣝ⟶࡜ (b) ࢞ࢫᑒධࢳࣕࣥࣂ࣮[6][PCPࡢᵓ㐀࡜ྜᡂ]
UTSA-16 [K2Zn3(C6H4O7)2] ࡣள㖄ࠊ࣒࢝ࣜ࢘ཬࡧࢡ࢚ࣥ㓟࡟ࡼࡗ࡚ᵓᡂࡉࢀ࡚࠾ࡾࠊ⣽Ꮝᚄࡀ
3.35.4ύ2ࡢࢲ࢖ࣖࣔࣥࢻᆺ࡟⤌ࡳୖࡀࡗ࡚࠸ࡿPCP࡛࠶ࡿ(Fig.2(a))ࠋྛࢡ࢚ࣥ㓟ࡢ࢝ࣝ࣎ࣥ㓟ࡢ㓟⣲ࡣ୍ࡘࢆ㝖࠸࡚㔠ᒓࢆ୰ᚰ࡜ࡋࡋࡓඵ㠃య࡜ᅄ㠃యཬࡧK+ࢆ㓄఩ࡋ࡚࠸ࡿ(Fig.2(b))ࠋྜᡂ
┤ᚋࡢ≧ែ࡛ࡣྛK+࡟㸰ࡘỈࡀ㓄఩ࡋ࡚࠾ࡾࠊࡇࡢ㓄఩Ỉ࡟CO2ࡀ྾╔ࡍࡿࡇ࡜ࡀሗ࿌ࡉࢀ࡚࠸
ࡿ[7]ࠋࡲࡓࠊ㓄఩Ỉࡢ⤖ྜࡣᙅࡃࠊ90Υࡢ ᗘ࡛1᪥┿✵஝⇱ࡍࡿࡇ࡜࡛᏶඲࡟㝖ཤࡍࡿࡇ࡜ࡀ
ฟ᮶ࡿࠋ௚࡟ࡶCO2ࡢ྾╔ࢧ࢖ࢺ࡜ࡋ࡚ࠊ㓄఩Ỉࢆ㝖ཤࡋࡓᚋࡢK+ࡸ㓄఩Ꮚ࡛࠶ࡿࢡ࢚ࣥ㓟ࡀண᝿ࡉࢀ࡚࠸ࡿ[7]ࠋ
㓑㓟ள㖄஧Ỉ࿴≀ࠊỈ㓟໬࣒࢝ࣜ࢘ཬࡧࢡ࢚ࣥ㓟ࢆ
H2O୰࡛ΰྜࡋࡓ⁐ᾮ࡟࢚ࢱࣀ࣮ࣝࢆຍ࠼࡚120Υ࡛2᪥ຍ⇕ࡋࠊUTSA-16ࡢ⢊ᮎࢆᚓࡓࠋᚓࡽࢀࡓ⢊ᮎࢆ࣓ࢱࣀ࣮࡛ࣝ3᪥Ὑίࡋࡓ
ᚋࠊᐊ ࡛24᫬㛫┿✵஝⇱ࡋࡓࡶࡢࢆ1࡜ࡍࡿࠋᮏ◊✲࡛ࡣ」ᩘ᮲௳࡛NMR ᐃࢆ⾜࠸ࠊCO2ࡸH2Oࡢ㐠ື

Fig. 2 (a) ⣽Ꮝࡢ኱ࡁࡉ(⅊⅊෇ࡣ྾╔㒊఩)࡜
࡜ (b) UTSA-16 ࡢࢡ࢚ࣥ㓟࿘ࡾࡢᵓ㐀

ࢆㄪ࡭ࡓ(Table 1)ࠋ

－ 317 －      Table 1 ヨᩱࡢᚋฎ⌮[NMR ᐃ᮲௳]ࢧࣥࣉࣝྡ1࠿ࡽࡢㄪᩚ

1_assyn

D2O࡟12᫬㛫᭚㟢ࡋH2OࢆD2O࡟஺᥮

ᮏ㟁ᏊࡢJNM-ECA300ศගჾࢆ

1a90Υ࡛10᫬㛫┿✵஝⇱ࡋ࡚H2O㝖ཤᚋ⏝࠸࡚ࠊ7 T㉸ఏᑟ࣐ࢢࢿࢵࢺ࡜

1a_D2O(1h)90Υ࡛10᫬㛫┿✵஝⇱ࡋ࡚H2O㝖ཤᚋࠊࡍ࡭࡚ࡢᅛయNMRᐇ㦂ࡣࠊ᪥

4 mm MASࣉ࣮ࣟࣈ࡟ࡼࡾᐊ ࡛
⾜ࡗࡓࠋ1

13

Hࠊ C MAS NMR ᐃ

D2O࡟1᫬㛫᭚㟢
1a_D2O(12h)ࡣヨᩱᅇ㌿㏿ᗘ5 kHz࡛ ᐃࡋࡓࠋUTSA-16࡟྾╔ࡉࡏࡿCO2ࡣ

90Υ࡛10᫬㛫┿✵஝⇱ࡋ࡚H2O㝖ཤᚋࠊ
D2O࡟12᫬㛫᭚㟢

1a_D2O + CO2

13Cྠ఩య⨨᥮ࡋࡓࡶࡢࢆ⏝࠸

90Υ࡛10᫬㛫┿✵஝⇱ࡋ࡚H2O㝖ཤᚋࠊ
D2O࡜CO2ࡢΰྜ࢞ࢫ࡟30ศ᭚㟢ࡓࠋ‵₶㞺ᅖẼୗࡢỈࡢ㐠ືࢆ▱ࡿࡓࡵ࡟ࠊH2Oࡢ௦ࢃࡾ࡟D2Oࢆ⏝࠸࡚2H NMR ᅄᴟᏊ࢚ࢥ࣮ ᐃ㸦ヨᩱᅇ㌿㏿ᗘ0 Hz㸧ࢆ⾜ࡗࡓࠋ[UTSA-16ෆ㒊ࡢD2Oࡢ㐠ືᛶࠊཬࡧCO2࡜ࡢ➇தᛶ]྾╔㐣⛬࡟࠾ࡅࡿD2Oࡢ㐠ືᛶࢆㄪ࡭ࡿࡓࡵ࡟ࠊD2O࡟᭚ࡍ᫬㛫ࢆ1h࡜12h࡟ኚ࠼࡞ࡀࡽ2H
NMR ᐃࢆ⾜ࡗࡓ(Fig.3(a) ࠊᕥୖࡣつ᱁໬ࡋࡓᅗ㸧ࠋ1a_D2O(1h)ࡣಙྕᙉᗘࡀᙅ࠸࣌࢖ࢡࢲࣈ
ࣞࢵࢺࡢࣆ࣮ࢡࢆ♧ࡋࡓࠋD2Oࡢ྾╔㔞ࡣᑡ࡞ࡃࠊᅇ㌿㍈ࢆ᭷ࡍࡿ≉␗ⓗ࡞㐠ືࢆࡋ࡚࠸ࡿࡇ࡜
ࡀண᝿ࡉࢀࡿ[8]ࠋ୍᪉ࠊ1a_D2O(12h)࡟࠾࠸࡚ࠊ࣌࢖ࢡࢲࣈࣞࢵࢺ࡜➼᪉ⓗ࡞ࣆ࣮ࢡࡢ㔜ࡡྜࢃࡏࡀ☜ㄆ࡛ࡁࡓࠋ≉␗ⓗ࡞㐠ື࣮ࣔࢻࡢD2O࡟ຍ࠼࡚ࠊ➼᪉ⓗ࡞D2Oࡀ12hࡢ㛫࡟㏣ຍࡉࢀࡓ࡜ண
᝿ࡉࢀࡿࠋ୍⯡ⓗ࡟ࠊᴟᛶࡢ㧗࠸Ỉࡢ྾╔ࡣ⛊࠿ࡽศࡢ࣮࢜ࢲ࡛ᖹ⾮࡟㐩ࡍࡿࡀࠊUTSA-16ࡣࠊᩘ᫬㛫ࡢ㠀ᖖ࡟㛗࠸ࢱ࢖࣒ࢫࢣ࣮࡛ࣝD2Oࢆ྾╔ࡋࠊࡲࡓࡑࡢ྾╔ࡋࡓD2Oࡢ୍㒊ࡣࠊ≉␗ⓗ࡞㐠ື࣮ࣔࢻࢆ᭷ࡋ࡚࠸ࡿࡇ࡜ࡀ☜ㄆࡉࢀࡓࠋ
ḟ࡟CO2࡜D2Oࡢΰྜ࢞ࢫ࡟᭚㟢ࡋࡓ1a_D2O + CO2ࢆᑐ㇟࡟⾜ࡗࡓNMR ᐃࡢࢫ࣌ࢡࢺࣝࢆ
Fig.3(b)(c)࡟♧ࡍࠋ13C MAS NMR(Fig3.(b))࡛ࡣࢫ࣌ࢡࢺࣝ࡟࠾࠸࡚124.6ppm࡟CO2⏤᮶ࡢࣆ࣮ࢡ
ࢆ☜ㄆ࡛ࡁࡓࡀࠊ2H NMR(Fig3.(c))ࡣD2O⏤᮶ࡢࣆ࣮ࢡࢆ☜ㄆࡍࡿࡇ࡜ࡀฟ᮶࡞࠿ࡗࡓࠋ

Fig. 3 (a) D2O ᭚㟢ࡋࡓࢧࣥࣉࣝࢆᑐ㇟࡜ࡋࡓ 2H NMR ࢫ࣌ࢡࢺࣝࠊ
ࠊ(b) ΰྜ࢞ࢫ࡟᭚㟢ࡋࡓࢧࣥࣉࣝࢆᑐ㇟࡜ࡋࡓ 13C MAS NMR ࢫ࣌ࢡࢺࣝ࡜ࠊ(c) 2H NMR ࢫ࣌ࢡࢺࣝ

－ 318 －

[㓄఩Ỉࡢ᭷↓࡟ࡼࡿᵓ㐀ኚ໬]ୖグࡢ≉␗ⓗ࡞CO2ࡢඃඛ྾╔ࡢᶵᵓࢆ᫂ࡽ࠿
࡟ࡍࡿࡓࡵ࡟ࠊ㓄఩Ỉࡢ㝖ཤ࡟ࡼࡿᒁᡤᵓ㐀ࡢኚ໬ࢆㄪ࡭ࡓࠋ1aࠊ1a_D2O(12h)ࠊ1a_assynࡢ13C
CP-MAS NMRࡢࢫ࣌ࢡࢺࣝࢆFig.4࡟♧ࡍࠋD2O
ࡀᏑᅾࡋ࡞࠸1aࡣࢡ࢚ࣥ㓟ࡢCH2ࢆ♧ࡍ50ppm௜
㏆ࡢࣆ࣮ࢡࡀ1ᮏ࡞ࡢ࡟ᑐࡋ࡚ࠊD2Oࡀ྾╔ࡋ࡚
࠸ࡿ1a_D2O(12h) , 1_assyn ࡣࢡ࢚ࣥ㓟ࡢCH2ࢆ♧ࡍ50ppm௜㏆ࡢࣆ࣮ࢡࡢࢩࣇࢺ࡜ศ⿣໬ࢆ☜ㄆࡋࡓࠋ㓄఩Ỉࡢ㝖ཤ࡟ࡼࡗ࡚ᒁᡤᵓ㐀ࡀኚ໬ࡋࠊ
D2OࡼࡾCO2ࢆඃඛⓗ࡟྾╔ࡍࡿ≉Ṧ࡞␯Ỉⓗ࡛࠶ࡿ⣽Ꮝࡀฟ᮶ࡓࡇ࡜ண᝿ࡉࢀࡿࠋXRDࣃࢱ࣮ࣥ࡟࠾࠸࡚ࡶࢃࡎ࠿࡞ࣆ࣮ࢡኚ໬ࡀ☜ㄆࡉࢀ࡚
࠾ࡾࠊNMRࡢ⤖ᯝࢆᨭᣢࡋ࡚࠸ࡿࠋ
ඛ⾜◊✲࡛ࡣࠊH2O࡜CO2ࡢΰྜ⣔࡟࠾࠸࡚㓄఩Ỉ
ࡀCO2ࡢ྾╔ࢧ࢖ࢺ࡜⪃࠼ࡽࢀ࡚࠸ࡓࠋࡋ࠿ࡋᮏ◊✲࡟ࡼࡾ㓄఩Ỉࢆ㝖ཤࡋࡓUTSA-16ࡣࠊD2Oࢆᐜ᫆

Fig. 4 D2O ᭚㟢ࡋࡓࢧࣥࣉࣝ࡜஝⇱≧ែࡢࢧࣥࣉࣝࢆᑐ㇟࡜ࡋࡓ 13C CP-MAS
NMR ࢫ࣌ࢡࢺࣝ

࡟྾╔ࡏࡎࠊࡑࡢ㛫ࡣ㓄఩ࢧ࢖ࢺࡣ✵࡟࡞ࡿࠋࡑࡢሙྜࠊࡑࡢK+ࡢ㓄఩ࢧ࢖ࢺ࡟ࢡ࢚ࣥ㓟ࡢ࢝ࣝ࣎ࣥ㓟ࡀ㓄఩ࠊཬࡧ㓄఩࡟ࡼࡿࢡ࢚ࣥ㓟࿘ࡾࡢᒁᡤᵓ㐀ኚ໬ࡀண᝿ࡉࢀࡿࠋࡑࡢࡓࡵࠊ㓄఩Ỉࡀ↓࠸UTSA-16ࡣぶỈᛶࡢ㧗࠸K+ࡢ྾╔ࢧ࢖ࢺ㸦㓄఩ࢧ࢖ࢺ㸧ࡣࢡ࢚ࣥ㓟࡛༨᭷ࡉࢀ࡚࠾ࡾࠊỈࡀ྾╔ࡋ࡟ࡃࡃ࡞ࡗࡓ࡜⪃࠼࡚࠸ࡿࠋࡲࡓࠊCO2ࡢ྾╔ࢧ࢖ࢺࡣ᫂ࡽ࠿࡟࡞ࡗ࡚࠸࡞࠸ࡀࠊࡑࢀࡽ
␯Ỉⓗ࡞⣽Ꮝ࡟CO2ࡀඃඛⓗ࡟྾╔࡛ࡁࡿࢧ࢖ࢺࡀ࠶ࡿ࡜⪃࠼ࠊゎᯒࢆ㐍ࡵ࡚࠸ࡿࠋ
[ࡲ࡜ࡵ]ᮏ◊✲࡛ࡣPCP࡟D2O࡜CO2ࡢΰྜ࢞ࢫࢆᑒධࡋ࡚MAS NMRࢆ⾜࠸ࠊ஝⇱≧ែࡢUTSA-16ෆ㒊
࡛ࡣD2O࡟ᑐࡋ࡚CO2ࡀඃඛⓗ࡟྾╔ࡉࢀࡿࡇ࡜ࢆ᫂ࡽ࠿࡟ࡋࡓࠋ2H NMR ᐃ࡟࠾࠸࡚ࠊD2Oࡢ
␗ᖖ࡟㛗࠸྾╔᫬㛫ࠊࡑࡋ࡚≉␗ⓗ࡞㐠ື࣮ࣔࢻࢆ᭷ࡍࡿ㓄఩Ỉ࡜➼᪉ⓗ࡞ᅇ㌿ࢆࡋ࡚࠸ࡿỈࡀΰᅾࡋ࡚࠸ࡿࡇ࡜ࢆࡀ᫂ࡽ࠿࡜࡞ࡗࡓࠋࡲࡓࠊ஝⇱≧ែ࡜D2O᭚㟢ࡋࡓUTSA-16ࡢẚ㍑࡟ࡼࡾ
D2OࡢᏑᅾࡢ᭷↓࡛ࢡ࢚ࣥ㓟࿘ࡾࡢᵓ㐀ࡀኚ໬ࡋ࡚ᒁᡤᵓ㐀࡟ṍࡳࡀ⏕ࡌࡿࡇ࡜࡟ࡼࡾࠊ␯Ỉⓗ࠿ࡘCO2ࢆඃඛⓗ࡟྾╔࡛ࡁࡿ⣽Ꮝࡀ࠶ࡿ࡜ண᝿ࡋ࡚࠸ࡿࠋ
[Reference][1] S. Kitagawa, R. Kitaura, S. Noro, Angew. Chem. Int. Ed., 2004, 43, 2334
[2] B. Chen, M. Eddaoudi, S. T. Hyde, M. O’Keeffe, O. M. Yaghi, Science 2001, 291, 1012
[3] N. T. T. Nguyen, H. Furukawa, F. Gȝndara, H. T. Nguyen, K. E. Cordova, O. M. Yaghi, Angew. Chem.
Int. Ed., 2014, 53, 10645[4] M. Inukai, M. Tamura, S. Horike, M. Higuchi, S. Kitagawa, K. Nakamura, Angew. Chem. Int. Ed.,2018, 57, 8687
[5] S. Xiang, Y. He, Z. Zhang, H. Wu, W. Zhou, R. Krishna, B. Chen , Nat. Comm., 2012, 3, 954[6] T. Kurihara, M. Inukai, M. Mizuno, J. Phys. Chem. Lett., 2022, 13, 7023
[7] A. Masala, F. Grifasi, C. Atzori, J. G. Vitillo, L. Mino, F. Bonino, M. R. Chierotti, S. Bordiga, J. Phys.
Chem. C., 2016, 120, 12068[8] T. Iijima, M. Mizuno, Chem. Phys. Lett., 2003, 380, 736－ 319 －

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ᅛయ 105 ࡟ࡼࡿ =Q⤖ྜᆺ 7D+H5 ࡢᵓ㐀ゎᯒ‫⇃ۑ‬㇂ဏ㔛㕥ᮌࡋࡪࡁ㸪㛗ᓥᩄ㞝㸪ᒣᓮಇኵ㸪∦ᒣ⪔኱㸪⚄ྲྀ⚽ᶞ㸪ᕝᮧฟ ᶓ὾ᅜ❧኱Ꮫ ⌮◊኱Ꮫ㝔⌮ᕤᏛᗓ

56& ྡྂᒇᕤᴗ኱Ꮫ

Solid-state NMR study of membrane embedded TaHeR in the presence of Zn 2+‫ۑ‬Sari Kumagai1, Shibuki Suzuki1, Toshio Nagashima2, Toshio Yamazaki2, Kota Katayama3, Hideki
Kandori3, Izuru Kawamura1
1

Graduate School of Engineering Science, Yokohama National University, Japan, 2RIKEN RSC, Japan,

3

Nagoya Institute of Technology, Japan.
Heliorhodopsin (HeR) is a transmembrane protein with a retinal chromophore that constitutes a new

rhodopsin family [1]. FTIR spectroscopy has revealed that only helical structural perturbations are observed
by binding Zn2+ to TaHeR [3]. Here, using solid-state NMR spectroscopy, we investigated whether the
structure of membrane embedded TaHeR in POPE/POPG is affected by Zn2+-binding. We exhibited Zn2+
concentration dependance of changes in 15N NMR signals of His imidazole rings using 15N3 His-labeled
sample. On the other hand, no peak shift of the retinal protonated Schiff base was observed using 15N Lyslabeled sample. From our results, we assume that the binding site of Zn2+ is located at His residues in thecytoplasmic region, distant from the retinal chromophore. This binding might contribute to the unknown
function of HeR, which is thought to be signal transduction due to the long photocycle.
࠙⥴ゝࠚࣟࢻࣉࢩࣥ࡜ࡣࣞࢳࢼ࣮ࣝⓎⰍᅋࢆ᭷ࡋࠊྍどᇦ࡟྾཰ࢆࡶࡘ 7 ᅇ⭷㈏㏻ᆺࢱࣥࣃࢡ㉁࡛࠶ࡿࠋ㏆ᖺࠊᚤ⏕≀ᆺ࠾ࡼࡧື≀ᆺࣟࢻࣉࢩࣥ࡜ࡣ඲ࡃ␗࡞ࡿᛶ㉁ࢆᣢࡘ᪂ࡋ࠸ࣟࢻࣉ
ࢩࣥ⩌࡜ࡋ࡚࣊ࣜ࢜ࣟࢻࣉࢩࣥ(HeR)ࡀⓎぢࡉࢀࠊ⤖ᬗᵓ㐀ࡀሗ࿌ࡉࢀࡓ[1,2]ࠋࡲࡓࠊFTIR ࡟ࡼࡾ Zn2+࡜≉␗ⓗ࡟⤖ྜࡍࡿࡇ࡜ࡀᥦၐࡉࢀ
[3]ࠊHeR ࡢᶵ⬟࡜ࡢ㛵ಀࡀὀ┠ࡉࢀ࡚࠸ࡿࠋᮏ
◊✲࡛ࡣࣄࢫࢳࢪࣥ(His)ࡢ࢖࣑ࢲࢰ࣮ࣝ⎔ࡢಙྕࡀ࢖࢜ࣥ⤖ྜ࡟ᩄឤ࡛࠶ࡿࡇ࡜࡟ὀ┠ࡋࠊ⬡㉁஧㔜⭷࡟෌ᵓᡂࡋࡓ 15N3-His ᶆ㆑ TaHeR ࡢ
NMR ಙྕࡢ Zn2+⃰ᗘ౫Ꮡᛶࢆㄪᰝࡋࡓ(Fig. 1)ࠋ

Fig. 1. Crystal structure of TaHeR (dimer)ࣟࢻࣉࢩࣥ, ᅛయ NMR, ࣄࢫࢳࢪࣥ
ࠐࡃࡲࡀ࠸ࡉࡾ, ࡍࡎࡁࡋࡪࡁ, ࡞ࡀࡋࡲ࡜ࡋ࠾, ࡸࡲࡊࡁ࡜ࡋ࠾, ࠿ࡓࡸࡲࡇ࠺ࡓ,࠿ࢇ࡝ࡾࡦ࡛ࡁ, ࠿ࢃࡴࡽ࠸ࡎࡿ

－ 322 －

࠙ᐇ㦂ࠚThermoplasmatales archaeon ⏤᮶ࡢ࣊ࣜ࢜ࣟࢻࣉࢩࣥ TaHeR ࢆࢥ࣮ࢻࡍࡿࣉࣛࢫ࣑ࢻ DNA
ࢆ኱⭠⳦ BL21 ᰴ࡟ᙧ㉁㌿᥮ࡋࠊM9 ᇵᆅ࡟ࡼࡾᇵ㣴ࢆ⾜ࡗࡓࠋall-trans ᆺࣞࢳࢼ࣮ࣝ࡜ 15N3-Hisࢆຍ࠼ࡓᚋ࡟ IPTG ࡟ࡼࡿⓎ⌧ㄏᑟࢆ⾜࠸ࠊ[15N3-His] TaHeR ࢆ኱㔞Ⓨ⌧ࡉࡏࡓࠋ[15Nİ-Lys] TaHeR࡟ࡘ࠸࡚ࡶྠᵝ࡟⾜ࡗࡓࠋPOPE:POPG=3:1 ࡢ࣏ࣜࢯ࣮࣒࡟ࢱࣥࣃࢡ㉁࡜⬡㉁ࢆ 1:20 ࡢࣔࣝẚ࡛⭷࡟෌ᵓᡂࡋࠊྛヨᩱࢆ Zn2+⃰ᗘࢆ 0, 0.10, 0.15, 0.20, 0.30, 0.40, 0.50, 1.0 mM ࡟ㄪ〇ࡋࡓ pH 7.0 ࡢ
Buffer ࡛⨨᥮ࡋ࡚Ỉ࿴⭷ヨᩱ࡜ࡋࡓࠋࡑࡢᚋࠊࢪࣝࢥࢽ࢔〇ヨᩱ⟶࡟ࣃࢵ࢟ࣥࢢࡋ࡚ 4.0 mm E-free
1

H-13C-15N ୕㔜ඹ㬆ࣉ࣮ࣟࣈࢆഛ࠼ࡓ 600 MHz ࡢศගィ (Bruker Avance რ)ࢆ⏝࠸࡚ 15N CP-MAS
ᐃࢆ⾜ࡗࡓࠋ ᐃ᮲௳ࡣᬯ≧ែ࡛ MAS ᅇ㌿ 12 kHzࠊࣉ࣮ࣟࣈ ᗘࢆ 278 K ࡜ࡋࡓࠋࡲࡓࠊ3 ḟ

ඖ NMR ࢹ࣮ࢱࢆ⏝࠸࡚ His ṧᇶࡢᖐᒓࢆ⾜ࡗࡓࠋ15N ࡢᇶ‽≀㉁ࡣ NH4Cl (38.34 ppm)࡜ࡋࡓࠋ
࠙⤖ᯝ࠾ࡼࡧ⪃ᐹࠚ[15Nİ-Lys] TaHeR ࡢ 15N CPMAS NMR ࢫ࣌ࢡࢺࣝࡼࡾࠊࣞࢳࢼ࣮ࣝࡢࣉࣟ
ࢺࣥ໬ࢩࢵࣇሷᇶ(RPSB)ࡢ໬Ꮫࢩࣇࢺ್ࡀ 178.9
ppm ࡜ᖐᒓࡉࢀࡓࠋࣔࢹࣝ໬ྜ≀࡛࠶ࡿ all-transࣞࢳࢽࣜࢹࣥ࡜ࣁࣟࢤࣥ໬≀࢖࢜ࣥ࡟࠾ࡅࡿRPSB ࡢ໬Ꮫࢩࣇࢺ್࡟ᑐࡍࡿᴟ኱྾཰Ἴ㛗ࡢኚ໬ࡣ┤⥺㛵ಀࢆ♧ࡋࠊከࡃࡢࣟࢻࣉࢩࣥࡣࡇ
ࡢࢺࣞࣥࢻࢆ♧ࡍࡀࠊTaHeR ࡣእࢀ࡚࠸ࡿ(Fig.
2)ࠋࡇࢀࡣ௚ࡢࣟࢻࣉࢩࣥ࡜␗࡞ࡾࠊSer112 ࡸ

Fig. 2. Relationship between 15N chemical shift

Ser234 ࡀ RPSB ࡢ❅⣲࡟᥋㏆ࡋ࡚࠸ࡿ࠿ࡽ࡛࠶

of RPSB and Ȝmax (TaHeR: 178.9 ppm/542 nm)

2+ࡿ࡜⪃࠼ࡽࢀࡿࠋZn ⤖ྜ࡟ࡼࡿ RPSB ࡢಙྕኚ໬ࡀほ ࡉࢀ࡞࠿ࡗࡓࡇ࡜࠿ࡽࠊࣞࢳࢼ࣮ࣝ
㏆ഐ࡟≉␗ⓗ⤖ྜ㒊఩ࡀᏑᅾࡋ࡞࠸ࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ୍᪉ࠊ[15N3-His] TaHeR ࡢ 15N CP-MASࢫ࣌ࢡࢺࣝ(Fig. 3)ࡼࡾࠊ୺㙐࢔࣑ࢻ NH࣭࢖࣑ࢲࢰ࣮ࣝ H-NH2࣭NG1 ࡢ఩⨨࡟ࣞࢳࢼ࣮ࣝ㏆ഐ
ࡢ His23, His82 ࡞࡝ࢆྵࡴඛ㗦࡞ಙྕࢆほࡋࡓࡀࠊ[Zn2+]౫Ꮡᛶࡣぢࡽࢀ࡞࠿ࡗࡓࠋ୍᪉࡛
210 ppm ௜㏆࡟ NG1 ࡬ࡢ Zn2+ࡢ⤖ྜ࡟⏤᮶ࡍࡿࣆ࣮ࢡ[4]ࢆ᳨ฟࡍࡿ࡜࡜ࡶ࡟ࠊH-NH2 ࡢ㡿ᇦࡢ
158 ࠾ࡼࡧ 170 ppm ࡟[Zn2+]౫Ꮡⓗ࡞ಙྕኚ໬ࡀ
ほࡉࢀࡓࠋࡇࢀࡣ Zn2+ࡀ His ࡢ࢖࣑ࢲࢰ࣮ࣝ

⎔ෆࡢG1 ఩ࡢ❅⣲࡟⤖ྜࡋࠊ㐠ືᛶࡀపୗࡋ࡚
CP ᳨ฟࢆྍ⬟࡟ࡋࡓ࡜♧၀ࡉࢀࡿࠋࡇࢀࡽࡢ⤖ᯝ࠾ࡼࡧ [U-13C,15N] TaHeR ࡢከḟඖ NMR ࢹ࣮ࢱ࡞࡝࠿ࡽ⣽⬊㉁ഃ࡟఩⨨ࡍࡿ His100 ࡀ Zn2+࡜ࡢ≉␗ⓗ࡞⤖ྜࢆᢸ࠺ྍ⬟ᛶࡀ♧၀ࡉࢀࡓࠋ

Fig. 3. 15N CP-MAS NMR spectra([15N3-His] TaHeR)࠙ཧ⪃ᩥ⊩ࠚ[1] A. Pushkarev et al. (2018) Nature, 558, 595. [2] W. Shihoya et al. (2019) Nature, 574, 132.
[3] M. Hashimoto et al. (2020) JPC Lett. 11, 8604. [4] S. S. Kidambi et al. (2003) Inorg. Chem. 42, 3142.

－ 323 －

P85

ᅛయNMRࢆ⏝࠸ࡓᖹ㠃ᅄ㓄఩ⓑ㔠(II)㘒యࡢศᏊ㐠ືࡢゎᯒ࡜ࡑࡢእ㒊่⃭ᛂ⟅ᛶ‫ۑ‬㔜⏣ὈᏹࠊỈ㔝ඖ༤㔠ἑ኱Ꮫ࣭ࢼࣀ࣐ࢸࣜ࢔ࣝ◊✲ᡤ

Stimuli response of molecular dynamics on square-planar Pt(II) complexes analyzed bysolid-state NMR‫ۑ‬Yasuhiro Shigeta, Motohiro Mizuno
Nanomaterials Research Institute, Kanazawa University
Stimuli-reponsive materials have been attracted much attention because of their potentially utilizationsuch as for sensors, actuators. Usually, discussions for molecular crystal-based stimuli-responsive materials
are based on their static states, such as crystal structure. On the other hand, molecular motion have been
increasing attention to affect property of materials. Herein, we report the grinding-induced molecular
dynamics changing of Pt(II) complex [PtCl2(BdmPhambpy)] (= 1; BdmPhambpy = bipyridine-4,4’-bis-3,5dimethylcarboxamide), investigated by solid-state 2H NMR spectroscopy.
The as-synthesized, deuterated complex 1 exhibited two sets of signals in the solid-state 2H NMR
measurement. These signals could be assigned to the fast rotational motion of methyl deuterons with small
angle librational motion and static state of phenyl deuterons. After grinding, additional signals wereobserved in the 2H NMR spectra, suggested grinding induced promotion of molecular dynamics.
࠙ᗎㄽࠚ㏆ᖺࠊእ㒊่⃭࡟ࡼࡗ࡚ࡑࡢᛶ㉁ࢆኚ໬ࡉࡏࡿ≀㉁⩌ࡢ◊✲ࡀ┒ࢇ࡟⾜ࢃࢀ࡚࠸ࡿࠋࡇ
ࡢᛶ㉁ࡣࠊࢭࣥࢧ࣮ࡸ࢔ࢡࢳ࢚࣮ࣗࢱ࣮➼࡬ࡢᒎ㛤ࡀᮇᚅࡉࢀ࡚࠾ࡾࠊእ㒊่⃭࡜ኚ໬ࡉࡏࡽࢀ
ࡿᛶ㉁࡟ࡣከᩘࡢ⤌ࡳྜࢃࡏࡀ࠶ࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࠋศᏊ⤖ᬗࢆ⏝࠸ࡓእ㒊่⃭ᛂ⟅ᛶ≀㉁࡟࠾ࡅࡿᛂ⟅ࡣࠊከࡃࡢሙྜእ㒊่⃭༳ຍ࡟ࡼࡿ⤖ᬗᵓ㐀ࡢኚ໬ࢆ୰ᚰ࡟㆟ㄽࡀᒎ㛤ࡉࢀ࡚࠾ࡾࠊ㟼ⓗ࡞≧ែࡢゎᯒࡀ୺࡛࠶ࡗࡓࠋ௚᪉ࠊศᏊ㐠ືᛶࡣ࢖࢜ࣥఏᑟᛶ࡞࡝⤖ᬗᵓ㐀ࡔࡅ࡛ࡣㄝ
᫂ࡀࡘࡅࡽࢀ࡞࠸ࡼ࠺࡞≀ᛶ࡟ᙳ㡪ࢆ୚࠼࡚࠸ࡿࡇ࡜ࡀ▱ࡽࢀ࡚࠸ࡿࠋእ㒊่⃭༳ຍ࡟ࡼࡗ࡚ศ
Ꮚ㐠ືࡀไᚚ࡛ࡁࢀࡤࠊ௒ࡲ࡛࡟↓࠸እ㒊่⃭ᛂ⟅ᛶ≀㉁ࡢ๰〇࡟⧅ࡀࡿྍ⬟ᛶࡀ࠶ࡿࠋ ᮏ◊✲࡛ࡣࠊࡍࡾ₽ࡋ࡟ࡼࡿ⤖ᬗᛶࡢపୗࡀศᏊ㐠ືࡸࡑࡢ㏿ᗘ࡟࡝ࡢࡼ࠺࡞ᙳ㡪ࢆཬࡰࡍ࠿
ࢆ2H ᅛయNMRཬࡧX⥺ᵓ㐀ゎᯒ࠿ࡽ㆟ㄽࡍࡿࡇ࡜ࢆ┠ⓗ࡟ࠊࡍࡾ₽ࡋ࡟ࡼࡿ⤖ᬗᛶࡢపୗࡸ㠀ᬗ㉁໬ࡀᩘከࡃሗ࿌ࡉࢀ࡚࠸
ࡿⓑ㔠(II)㘒యࡢ㓄఩Ꮚࢆ㔜Ỉ⣲໬ࡋࠊ㐠ືᛶࡢኚ໬࡟ࡘ࠸࡚ㄪ
࡭ࡓࡢ࡛ሗ࿌ࡍࡿࠋ
࠙ྜᡂࠚ㓄఩ᏊBdmPhambpyࡣࠊbipyridine-4,4’-dicarboxylic acidࢆሷ໬ࢳ࢜ࢽࣝ࡟ࡼࡗ࡚㓟ሷ໬≀࡬࡜ኚ᥮ࡋࠊ3,5dimethylaniline(dmAn)࡜཯ᛂࡉࡏࡿࡇ࡜࡛ྜᡂࡋࡓࠋdmAnࡣࠊ

Fig.1 Molecular structure of 1.

㓟໬ⓑ㔠(IV)Ꮡᅾୗ㔜Ỉࢆ⏝࠸࡚Ỉ⇕᮲௳࡛཯ᛂࡉࡏࡿࡇ࡜࡛㔜Ỉ⣲໬ࡋࡓࡶࡢࢆ⏝࠸ࡓࠋ᭦
࡟ࠊK2PtCl4࡜㓄఩Ꮚ࡜཯ᛂࡉࡏࡿࡇ࡜࡛┠ⓗ㘒య࡛࠶ࡿ[PtCl2(BdmPhambpy)] (=㘒㘒య1)ࢆྜᡂࡋ
ࡓ(Fig.1)ࠋ⁐ᾮ1H NMR ᐃࡢ⤖ᯝࠊ㘒యࡣdmAn㒊఩ࡢࣇ࢙ࢽࣝ㔜Ỉ⣲ࡀ85%ࠊ࣓ࢳࣝ㔜Ỉ⣲ࡀ
50%⛬ᗘ㔜Ỉ⣲໬ࡉࢀ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ
2H

ᅛయNMR, ⤖ᬗᵓ㐀‫ࢁࡦࡍࡸࡓࡆࡋۑ‬㸪ࡳࡎࡢࡶ࡜ࡦࢁ

－ 324 －

࠙⤖ᯝ࡜⪃ᐹࠚFig.2࡟ྜᡂࡋࡓ┤ᚋࡢ㘒㘒య1ࡢ100 rC࡟࠾ࡅࡿ2H NMRࢫ࣌ࢡࢺࣝࢆ♧ࡍࠋ2H NMRࢫ࣌ࢡࢺࣝࡣᅄᴟᏊ࢚ࢥ࣮ἲ
࡟ࡼࡗ࡚ ᐃࡋࡓࠋᚓࡽࢀࡓࢫ࣌ࢡࢺࣝࡣࠊ㧗㏿ᅇ㌿ࡋ࡚࠸ࡿ࣓ࢳࣝᇶࡀ࢔࣑ࢻᇶࡢC-N⤖ྜ᪉ྥࢆ㍈࡟᣺ືゅ27r
࡛᣺ືࡋ࡚࠸ࡿs18 kHz௜㏆࡟ࣆ࣮ࢡࢆ♧ࡍࢩࢢࢼࣝ࡜ࠊ
ྠᵝ࡟᣺ືࡋ࡚࠸ࡿࣇ࢙ࢽࣝ⎔ୖࡢ㔜Ỉ⣲ཬࡧ㍈ୖ࡟Ꮡᅾࡍࡿࡓࡵ࡟㐠ືࡋ࡚࠸࡞࠸㔜Ỉ⣲࡜ᖐᒓࡉࢀࡿPake pattern
ࡢࠊ3✀㢮ࡢࢩࢢࢼࣝࡢ㔜ࡡྜࢃࡏ࡛෌⌧࡛ࡁࡓࠋḟ࡟ࠊ㘒㘒య1ࢆࡍࡾ₽ࡋࡓ㝿ࡢኚ໬ࢆㄪ࡭ࡓ(Fig. 3)ࠋ
XRD ᐃࡢ⤖ᯝࠊ㘒㘒య1ࡣࡍࡾ₽ࡍ๓ࡣ⤖ᬗᛶࡀⰋ࠸ࡇ
࡜ࢆ♧ࡍከᩘࡢࢩ࣮ࣕࣉ࡞ࣆ࣮ࢡࢆ♧ࡋࡓ୍᪉ࠊࡍࡾ
₽ࡋ࡟ࡼࡗ࡚ࡇࢀࡽࡀࣈ࣮ࣟࢻ໬ࡋ࡚ほ ࡉࢀࡓࡇ࡜

Fig.2 2H NMR spectra of as-synthesized
1 (solid line) compared with simulated
spectra (dashed line).

࠿ࡽࠊ⤖ᬗᛶࡢⴭࡋ࠸పୗࡀ☜ㄆࡉࢀࡓ(Fig.3(a))ࠋ
⤖ᬗᛶࡢపୗࡀ㐠ືᛶ࡟୚࠼ࡿᙳ㡪ࢆㄪ࡭ࡿ࡭ࡃࠊங㖊ࢆ⏝࠸࡚ࡍࡾ₽ࡋࡓࢧࣥࣉࣝ࡟ࡘ࠸࡚
෌ᗘᅛయ2H NMRࢫ࣌ࢡࢺࣝࢆ ᐃࡋࡓࠋங㖊ࢆ⏝࠸ࡓࡍࡾ₽ࡋ࡛ࡣࠊࢧࣥࣉࣝ୰࡛ࡍࡾ₽ࡋࡢᗘྜ࠸ࡀ␗࡞ࡿ㒊ศࡀඹᏑࡍࡿ࡜ண᝿ࡉࢀࡿࠋࡑࡢࡓࡵࠊࡍࡾ₽ࡋ๓࡜ྠࡌ

ᗘ࠿ࡘྠࡌᚅࡕ᫬

㛫ࢆ⏝࠸࡚ ᐃࡋࡓ⤖ᯝ࡟ࡘ࠸࡚ẚ㍑ࡋࡓ(Fig.3(b))ࠋᚅࡕ᫬㛫1⛊࡟࠾࠸࡚ᚓࡽࢀࡓࡍࡾ₽ࡋᚋࡢࢫ࣌ࢡࢺࣝࡢ⥺ᙧࡣࠊࡍࡾ₽ࡋ๓࡜ࡣ᫂☜࡟␗࡞ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋࡍࡾ₽ࡋᚋࡢࢫ࣌ࢡࢺࣝ
⥺ᙧࢆࢩ࣑࣮ࣗࣞࢩࣙࣥ࡟ࡼࡗ࡚ゎᯒࡋࡓ࡜ࡇࢁࠊࡍࡾ₽ࡋ๓ࡢᡂศ࡟ຍ࠼ࠊ࢔࣑ࢻ㒊఩ࡢC-N⤖ྜࢆ㍈᪉ྥ࡜ࡋ࡚ࡍࡾ₽ࡋ๓ࡼࡾࡶ኱ࡁ࡞ゅᗘ࡛᣺ືࡍࡿ㐠ືࢆ♧၀ࡍࡿs5.6 kHzࡢࣆ࣮ࢡ࡜ࠊࡑࢀࡼࡾࡶ᭦࡟㐠ືᛶࡢ㧗࠸ᡂศࡢᏑᅾࢆ♧ࡍ0 kHzࡢࣆ࣮ࢡࡀ᪂ࡓ࡟⏕ࡌ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋs15 kHz௜㏆ࡢࣇ࢕ࢵࢸ࢕ࣥࢢ࡜ࢩ࣑࣮ࣗࣞࢩࣙࣥࣃࢱ࣮ࣥ࡜ࡢ୙୍⮴ࡣ᭦࡞ࡿ㐠ືᡂศࡢᏑᅾࢆ♧၀ࡋ࡚࠸ࡿࡀࠊࡇࢀࡣࡍࡾ₽ࡋࡀᆒ୍࡛࡞࠸ࡇ࡜࡟⏤᮶ࡋ࡚ศᏊ࿘㎶ࡢ⎔ቃࡀከᵝ࡛࠶ࡾࠊᑡᩘࡢከᵝ࡞ᡂศࡀᏑᅾࡍࡿࡓࡵ࡜ண᝿ࡉࢀࡿࠋ௨ୖࡢ⤖ᯝࡼࡾࠊࡍࡾ₽ࡋ࡟కࡗ࡚
᪂ࡓ࡞ศᏊ㐠ືࡀㄏ㉳ࡉࢀࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓࠋࡇࢀࡣࠊ⤖ᬗᛶࡢపୗ࡟కࡗ࡚ศᏊ࿘㎶࡟✵㛫ࡀ⏕ࡌࡓࡇ࡜࡟⏤᮶ࡍࡿ࡜⪃࠼ࡽࢀࡿࠋ

Fig.3 (a) XRD pattern of as-synthesized (top) and ground (bottom) 1. (b) 2H NMR spectra of as-synthesized
1 (top) and ground(bottom) 1. Spectra were shown in solid lines compared with simulation (dashed lines).

－ 325 －P86Y

STD NMR࡟ࡼࡿTiO2⢏Ꮚ࡜ᢠ࢖ࣥࣇ࢚ࣝࣥࢨ࢘࢖ࣝࢫ࣌ࣉࢳࢻ
ࡢ┦஫స⏝ゎᯒ‫ۑ‬㕥ᮌᝆᩯ㸪ᒸᮧⱥಖ2, ᕝᮧฟ, 㕥ᮌᝆ21ᶓ὾ᅜ❧኱Ꮫ࣭኱Ꮫ㝔⌮ᕤᏛᗓ
2⚟஭኱Ꮫ࣭Ꮫ⾡◊✲㝔ᕤᏛ⣔㒊㛛࣭⏕≀ᛂ⏝໬Ꮫㅮᗙ

Analysis of interaction of TiO2 particles with anti-viral peptide using STD NMR‫ۑ‬Yuto Suzuki1, Hideyasu Okamura2, Izuru Kawamura1, Yu Suzuki2
1

Graduate School of Engineering Science, Yokohama National University

2 Department of Applied Chemistry and Biotechnology, Graduate School of Engineering, University of Fukui

Proteins and peptides give the surface of inorganic particle materials functionality. NMR technology isextremely useful in analyzing the interaction of biomolecules with inorganic nanoparticle surfaces andsaturation transfer difference (STD) NMR has revealed the interaction of titanium-binding peptides (TBPs)
with TiO2 nanoparticles. In this study, we analyzed the interactions with a fragment of urumin, an antiinfluenza virus peptide from the Indian frog, and TiO2 nanoparticle by STD NMR. The results suggested thatthe urumin fragment binds to the surface of TiO2 nanoparticles and interacts primarily at N-terminal Ile1 andArg11.
[⥴ゝ]ࢱࣥࣃࢡ㉁ࡸ࣌ࣉࢳࢻࡣ↓ᶵ⢏Ꮚᮦᩱ࡟ᑐࡋ࡚྾╔࣭จ⦰ࡍࡿ࡞࡝ࡋ࡚⢏Ꮚࡢ⾲㠃ᶵ⬟໬ࢆᯝࡓࡍࠋ≉࡟ࡑࡢ⾲㠃࡟ᑐࡋ࡚ᢠయࠊᢠ⏕≀㉁ࡶࡋࡃࡣᢠ⳦࣌ࣉࢳࢻ࡞࡝ࢆ⤖ྜࡉࡏࡿࡇ࡜࡛ࢥ࣮
ࢸ࢕ࣥࢢࡋࠊࢼࣀ⢏Ꮚ⾲㠃ࡢᶵ⬟ᛶྥୖ࡟㛵ࢃࡿ◊✲ࡀᗈࡃ࡞ࡉࢀ࡚࠸ࡿ[1]ࠋ୍᪉࡛ࠊ࣌ࣉࢳࢻ࡜
↓ᶵ⢏Ꮚᮦᩱࡢ㛫ࡢ」㞧࡞┦஫స⏝ࡢ⌮ゎࡀ୙༑ศ࡞ࡓࡵࠊ┠ⓗࡢ↓ᶵᮦᩱ࡟≉␗ⓗ࡞⤖ྜぶ࿴ᛶࢆᣢࡘ⏕⌮άᛶࢱࣥࣃࢡ㉁ࡸ࣌ࣉࢳࢻศᏊࢆ≉ᐃࡍࡿࡇ࡜ࡣᐜ࡛᫆ࡣ࡞࠸ࠋ↓ᶵࢼࣀ⢏Ꮚ⾲㠃࡜⏕యศᏊࡢ┦஫స⏝ࢆゎᯒࡍࡿୖ࡛ NMR ᢏ⾡ࡣᴟࡵ࡚᭷ຠ࡛࠶ࡾࠊSTD NMR ࢆ฼⏝ࡋࡓࢳࢱࣥ⤖ྜᛶ࣌ࣉࢳࢻ(TBP)࡜ TiO2 ࢼࣀ⢏Ꮚ࡜ࡢ┦஫స⏝ࡀሗ࿌ࡉࢀ࡚ࡁࡓ[2,3]ࠋ
ᮏ◊✲࡛ࡣࠊ࢖ࣥࢻ࢔࢚࢝࢞ࣝ⏤᮶ࡢᢠ࢖ࣥࣇ࢚ࣝࣥࢨ࢘࢖ࣝࢫάᛶ࣌ࣉࢳࢻ ࣑࢘ࣝࣥ(Urumin)ࡢࣇࣛࢢ࣓ࣥࢺ࣌ࣉࢳࢻ(୍ḟᵓ㐀: IPLRGAFINGRWDSQ)࡜ TiO2 ࢼࣀ⢏Ꮚ㛫࡟࠾ࡅࡿ┦஫స⏝࡟ࡘ࠸࡚ STD NMRᐃࢆ⏝࠸᳨࡚ウࡋࠊTiO2 ࢼࣀ⢏Ꮚ࡟ᑐࡍࡿ࣑࢘ࣝࣥࣇࣛࢢ࣓ࣥࢺ࣌

ࣉࢳࢻࡢᵓ㐀ゎᯒࢆ⾜ࡗࡓࠋ[ᐇ㦂᪉ἲ]
ᅛ┦ྜᡂἲ࡛ྜᡂࡉࢀࡓ࣑࢘ࣝࣥࡢࣇࣛࢢ࣓ࣥࢺࢆ‽ഛࡋࠊECA600II ศගィࢆ⏝࠸࡚ NMR ᐇ㦂ࢆ⾜ࡗࡓࠋNMR ಙྕࡢᖐᒓࡣ TOCSY, 1H-13C HSQC, ROESY

ᐃ࡛ᚓࡽࢀࡓࢫ࣌ࢡࢺࣝࢆ⏝࠸࡚⾜ࡗࡓࠋTiO2 ⾲㠃ࡢ⤖ྜỈ࠿ࡽ࣑࢘ࣝࣥ࡬ࡢ㣬࿴⛣ືࢆほ ࡍࡿࡓࡵࠊ⁐፹࡟ࡣ 10 % D2O/ 90 %H2O ࣜࣥ㓟⦆⾪ᾮ(pH : 6.8)ࢆ⏝࠸ࠊ࣌ࣉࢳࢻ 3.0 mM ࡜ TiO2 1 mg/mL ࡢ᮲௳࡛ ᐃࡋࡓࠋ㣬࿴ࣃࣝࢫ↷ᑕ఩⨨ࡣ on resonance ࢆ 4.7 ppmࠊoff resonance ࢆѸ10 ppm ࡟ࡑࢀࡒࢀタᐃࡋࡓࠋࡲࡓࠊ㣬࿴ࣃࣝࢫ↷ᑕ᫬㛫ࢆ0.8, 1.6, 2.4, 3.2, 4.8, 6.4, 8.0, 9.6, 11.2 s࡟ኚ࠼࡚ ᐃࢆ⾜࠸ࠊ㣬࿴ࣃࣝࢫ㠀↷ᑕࡢ
STD NMR㸪TiO2ࢼࣀ⢏Ꮚ, ᢠ࢖ࣥࣇ࢚ࣝࣥࢨ࢘࢖ࣝࢫ࣌ࣉࢳࢻ
‫࡜࠺ࡺࡁࡎࡍۑ‬, ࠾࠿ࡴࡽࡦ࡛ࡸࡍ, ࠿ࢃࡴࡽ࠸ࡎࡿ, ࡍࡎࡁࡺ࠺

－ 326 －NMR ࢫ࣌ࢡࢺࣝࡢࢩࢢࢼࣝᙉᗘ࡟ᑐࡍࡿ STD ࢩࢢࢼࣝᙉᗘࡢ๭ྜ(ASTD)ࢆồࡵࠊ㣬࿴ࣃࣝࢫ↷ᑕ᫬㛫࡟ᑐࡍࡿࣉࣟࢵࢺࢆ⾜࠸ࠊSTD buildup curve ࢆస〇ࡋࡓࠋ[⤖ᯝ࣭⪃ᐹ]࣑࢘ࣝࣥࡢࣇࣛࢢ࣓ࣥࢺࡢTOCSY NMRࢫ࣌ࢡࢺࣝࢆFig. 1࡟♧ࡍࠋ1H-13C HSQCཬࡧROESY
ᐃ࡟ࡼࡗ࡚ᚓࡽࢀࡓࢫ࣌ࢡࢺࣝࢆే⏝ࡍࡿࡇ࡜࡛ࠊ࣑࢘ࣝࣥࡢ1H NMRࢩࢢࢼࣝࢆFig. 1ࡢࡼ࠺࡟ᖐᒓࡋࡓࠋ㣬࿴ࣃࣝࢫ↷ᑕ᫬㛫11.2 s࡟࠾ࡅࡿ࢘ࣝ
࣑ࣥࣇࣛࢢ࣓ࣥࢺ-TiO2ヨᩱࡢSTD NMRࢫ࣌ࢡࢺࣝࢆFig. 2࡟♧ࡍࠋ࣌ࣉࢳࢻࡢࡳࡢヨ
ᩱ࡛ࡣSTDࢩࢢࢼࣝࡀほ ࡉࢀ࡞࠿ࡗࡓࡢ
࡟ᑐࡋࠊ࣌ࣉࢳࢻ-TiO2ヨᩱ࡛ࡣSTDࢩࢢࢼࣝࡀほ ࡉࢀࡓࡇ࡜࠿ࡽࠊTiO2⾲㠃ࡢ⤖ྜỈ࠿ࡽ࣑࢘ࣝࣥࣇࣛࢢ࣓ࣥࢺ࣌ࣉࢳࢻ࡬
㣬࿴⛣ືࡀ㉳ࡁ࡚࠸ࡿࡇ࡜ࡀほ ࡉࢀࡓࠋࡇࢀ࡟ࡼࡾTiO2⾲㠃࡟࣌ࣉࢳࢻࡀ┦஫స⏝ࡋ࡚࠸ࡿࡇ࡜ࡀ♧၀ࡉࢀࡓࠋ㣬࿴ࣃࣝࢫ㠀↷ᑕࡢ࣑࢘ࣝࣥࣇࣛࢢ࣓ࣥࢺ-TiO2 ヨᩱࡢ
1H NMRࢫ࣌ࢡࢺࣝࡢಙྕᙉᗘ࡟ᑐࡍࡿྛ

Fig. 1 TOCSY NMR spectrum of urumin fragment

STD NMRࢩࢢࢼࣝࡢ┦ᑐᙉᗘࢆẚ㍑ࡋࡓ
࡜ࡇࢁࠊ0.797, 0.939, 1.872, 2.998 ppm࡟ほ(3 mM peptide in 10 % D2O 20 mM phosphate bufferࡉࢀࡓࢩࢢࢼࣝࡢᙉᗘࡀẚ㍑ⓗ㧗ࡃ࡞ࡗ

pH 6.8, mixing time: 60 ms).

࡚࠸ࡓࠋࡋࡓࡀࡗ࡚ࠊN➃ࡢIle1ࡸArg11࡞
࡝ࡀTiO2 ࢼࣀ⢏Ꮚ࡜ࡢ┦஫స⏝࡟࠾࠸࡚㔜せ࡛࠶ࡿࡇ࡜ࡀ⪃࠼ࡽࢀࡿࠋࡲࡓࠊ㣬࿴ࣃࣝࢫ↷ᑕ᫬㛫ࡢቑ኱࡟కࡗ࡚ࠊSTDࢩࢢࢼࣝᙉ
ᗘࡀቑ኱ࡍࡿࡇ࡜ࡀ☜ㄆࡉࢀࡓࠋ
⌧ᅾࠊ㣬࿴ࣃࣝࢫ↷ᑕ᫬㛫ࢆኚ࠼࡚ ᐃࡋ
ࡓྛSTD NMRࢫ࣌ࢡࢺࣝ࠿ࡽస〇ࡋࡓSTD
buildup curveࢆ⏝࠸࡚ྛ 1H NMRࢩࢢࢼࣝ࡟
࠾ࡅࡿSTDຠᯝࢆồࡵ࡚࠾ࡾࠊᮏウㄽ఍࡟࡚࣑࢘ࣝࣥࣇࣛࢢ࣓ࣥࢺ-TiO2㛫࡟࠾ࡅࡿ┦஫స⏝㒊఩ࡢヲ⣽࡟ࡘ࠸࡚㆟ㄽࡍࡿணᐃ࡛࠶

Fig. 2 1D STD NMR spectrum with saturation time of 11.2 sof urumin fragment – TiO2 sample in solution.

ࡿࠋ
ཧ⪃ᩥ⊩

[1] Bahrami, A., Delshadi, R., Jafari, S. M. (2020) Trends Food Sci. Technol. 99, 217–228.
[2] Suzuki, Y., Shindo, H., Asakura, T. (2016) J. Phys. Chem. B, 120, 4600-4607.
[3] Suzuki, Y., Shindo, H. (2018) Polymer J., 50, 989-996.

－ 327 －

P87

105 ෾ੵͶ͕͜Ζӹରࢾྋ΃͹Πϕϫʖο͹୵ࡩ߶‫ ీࡋ˕  ߵ࠾ ڰ‬࿪஋  ྜྷ ࢛෋  ‫܊‬ഇ୉ָ ཀྵ޽ָ෨ ૱߻ཀྵ޽ָՌ ‫܊‬ഇ୉ָ‫حؽ‬෾ੵϜ΢ηνʖ ‫܊‬ഇ୉ָ ‫حؽ‬෾ੵιϱνʖ
Exploring approaches to liquid samples in NMR analysis
Sayaka Takahashi1,2 żKazuo Hosoda3 Fumio Hayashi3

1 School of Science and Technology, Faculty of Science and Engineering, Gunma University
2 Meister of Instrumental Analysis, Gunma University
3 Center for Instrumental Analysis, Gunma University
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‫حؽ‬෾ੵɼಋ࣢್॑؇ɼ෾ੵԿָɼ༻ӹ 105͖ͪͺ͢ ͠Ώ͖ɼ˕Άͨͫ ͖͕ͥɼͺΏ͢ ΀Ί͕－ 328 －

಼؇͹ '66 εήψϩ‫ౕک‬Ͷͯ͏ͱ ࢘༽͢ͱ͏Ζʤ‫ה‬ʥεΰϝ੣ 63 ಋ࣢؇ͺɼ಼؇ʀ֐؇಼Ͳ͹༲੷͗ΩνϫήͶ‫͠ࡎى‬Ηͱ͏Ήͤ͗؈ҝద͵‫ࢋܯ‬Ν໪దͶ‫خ‬६෼࣯ '66 ͹εήψϩ͹୉͘͠Νർֳ͢ͱೳౕ͹‫ࢋ׷‬ΝࢾΊΉͪ͢ɽ಼؇Νૢ೘͢͵͏য়ସͲ͹ '66 εήψϩͳɼͨ͹ '66 ༻ӹΝ಼؇Ͷ஭೘͢ɼ֐؇Ͷͺ॑ਭ͹ΊΝ஭೘ͪ͢ͳ͘͹ '66 εήψϩΝർֳ͢ɼͨ͹ർͳ͢ͱ  ഔɼͯΉΕ಼؇ '66 εήψϩͺɼ ഔ‫س‬ए͹য়ସͳಋ౵ͳ‫੷ݡ‬΍Ζ͞ͳ͗Ͳ͘Ήͪ͢ɽ ֐؇ʀ಼؇Ͳ͹εήψϩ͹ఈྖ੓ ಼؇ '66 εήψϩͳ֐؇͹໪ద෼εήψϩͳ͹੷෾஍͹ർͶͯ͏ͱɼ໪ద෼͹ೳౕͳ͹૮‫ؖ‬Ν֮೟͢Ήͪ͢ɽ֐؇Ͷ஭೘ͤΖγϱϕϩͺɼΩϓΥ΢ϱ͹॑ਭ༻ӹηφρέΝࡠ੔ɾ͖ͨ͞Δ෾஭‫س‬एΝ͢ɾ౵ഔ͕Γ;  ഔ͖Δ  ഔΉͲ͹‫س‬ए༻ӹΝ֐؇Ͷ஭೘ɼಋ಼ͣ؇Ͷͱ଎ఈ͢Ήͪ͢ɽԥ࣢ͶΩϓΥ΢ϱ͹ೳౕɾॐ࣢Ͷ֦ηϘέφϩ৏Ͳ '66 εήψϩͳΩϓΥ΢ϱεήψϩ͹
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͗Ͳ͘٠࿨ͤΖ͗Ͳ͘ΖՆ೵੓Νࣖͤࣆ͗Ͳ͘Ήͪ͢ɽ
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෨̑೧ਫ਼ʥͺɼ‫حؽ‬෾ੵιϱνʖ͹֐෨ғབ౵͹଎ఈ΍୴ͮͱ΍Δͮͱ͏Ήͤɽ－ 329 －

P88Y஧ḟᵓ㐀ࡢ␗࡞ࡿ⤌᥮࠼ࢡࣔ⣒ࢱࣥࣃࢡ㉁ࢤࣝࡢNMRᵓ㐀ゎᯒཬࡧᶵᲔⓗ≉ᛶホ౯‫ۑ‬ᮾᏕ᠇㸪బ⸨೺኱2, ᳃Ọ㝯ᚿ3, బ⸨ᾴ3, ᒸᮧⱥಖ1, 㕥ᮌᝆ1
1 ⚟஭኱Ꮫ኱Ꮫ㝔ᕤᏛ◊✲⛉2 Spiber Inc.
3 㭯ᒸᕤᴗ㧗➼ᑓ㛛Ꮫᰯ

NMR structural analysis and mechanical property evaluation of recombinant spider silk
protein gels with different secondary structures‫ۑ‬Takanori Higashi1, Takehiro K. Sato2, Takashi Morinaga3, Ryo Satoh3, Hideyasu Okamura1, Yu Suzuki1
1

Graduate school of Engineering, University of Fukui

2

Spiber Inc.

3

Department of Creative Engineering, National Institute of Technology, Tsuruoka College
Dragline silk produced by spiders as their lifeline has extraordinary mechanical properties. Recombinantspider silk protein (RSP) is produced by microorganisms, and regenerated fibers, nonwoven fabrics, and gelsprocessed from the RSP powder are developed. The primary structure of RSP, which mimics the natural
spider silk protein, repeats the poly-Ala and Gly-rich regions. In the fiber, the poly-Ala region, which forms
ȕ-sheet crystals, provides high strength [1]. Thus, if the secondary structure of the poly-Ala region is changed,
the physical properties of the materials obtained from RSP can be modified. In this study, we prepared RSP
hydrogels with different secondary structures and performed NMR structural analysis and mechanicalcharacterization. Consequently, we found a correlation between the secondary structure of poly-Ala region
and the mechanical properties of the RSP hydrogels. This correlation provides an insight into the productionof RSP gels with excellent mechanical properties.

Introductionࢡࣔࡢ⣳ࡂฟࡍ⣒ࡢ୰࡛ࡶࠊ⮬㌟ࡢ࿨⥘࡜ࡋ࡚⏝࠸ࡿ≌ᘬ⣒ࡣ㧗ᙉᗘ࣭㧗ᙎᛶࡢඃࢀࡓᶵᲔⓗ≉ᛶࢆ᭷ࡋ࡚࠸ࡿࠋ
⌧ᅾࠊᚤ⏕≀࠿ࡽ⤌᥮࠼ࢡࣔ⣒ࢱࣥࣃࢡ㉁㸦RSP㸧ࢆ⏕⏘ࡋࠊᚓࡽࢀࡓ⢊య࠿ࡽ⧄⥔ࠊ୙⧊ᕸࠊࢤࣝ➼ࢆస〇ࡍࡿᡂᙧຍᕤᢏ⾡ࡢ㛤Ⓨࡀ㐍ࡵࡽࢀ࡚࠸ࡿࠋኳ↛ࢡࣔ⣒ࢱࣥࣃࢡ㉁࠾ࡼࡧࡑࢀࢆᶍೌࡋࡓ RSP ࡢ࢔࣑ࣀ㓟㓄ิࡣ୺࡟ Ala
㐃㙐㡿ᇦ࡜ Gly ࣜࢵࢳ㡿ᇦࡀ⧞ࡾ㏉ࡉࢀ࡚࠾ࡾࠊȕ-sheet ⤖ᬗࢆᙧᡂࡍࡿ Ala 㐃㙐㡿ᇦࡣ㧗ᙉᗘࡢ≉ᛶࢆ⏕ࡳฟࡍ
㸦Fig. 1㸧ࠋࡑࡇ࡛ࡇࡢAla㐃㙐㡿ᇦࡢ஧ḟᵓ㐀ࢆኚ໬ࡉࡏࠊ
ᮦᩱࡢ≀ᛶࢆᨵኚ࡛ࡁࡿ࡜⪃࠼ࠊᮏ◊✲࡛ࡣᶵᲔⓗ≉ᛶ࡟ඃࢀࡓ RSP ࣄࢻࣟࢤࣝస〇ࡢᣦ㔪࡜࡞ࡿ▱ぢࢆᚓࡿࡓࡵࠊ

Fig. 1. Primary structure ofrecombinant spider silk protein.

ࢤࣝࡢ஧ḟᵓ㐀࡜ᶵᲔⓗ≉ᛶࡢ㛵ಀ࡟ࡘ࠸᳨࡚ウࢆ⾜ࡗࡓࠋࢡࣔ⣒ࢱࣥࣃࢡ㉁㸪ࢤࣝ‫ࡾࡢ࠿ࡓࡋࡀࡦۑ‬㸪ࡉ࡜࠺ࡓࡅࡦࢁ㸪ࡶࡾ࡞ࡀࡓ࠿ࡋ㸪ࡉ࡜࠺ࡾࡻ࠺㸪࠾࠿ࡴࡽࡦ࡛ࡸࡍ㸪ࡍࡎࡁࡺ࠺

－ 330 －

Experimental ᭷ᶵ⁐፹ฎ⌮࡟ࡼࡾ Ala 㐃㙐㡿ᇦࡀ random coil, ȕ-sheet, Į-helix ᵓ㐀ࢆᙧᡂࡋࡓ RSP ⁐ᾮࢆࡑࢀࡒࢀㄪ〇ࡋࠊ10%(w/w) RSP ࣄࢻࣟࢤࣝࢆస〇ࡋࡓࠋᚓࡽࢀࡓࢤࣝࢆࡑࢀࡒࢀ rc-RSP, ȕRSP, Į-RSP ࡜ࡍࡿࠋࢤࣝ࠾ࡼࡧࢤࣝࡢ෾⤖஝⇱య࡟ᑐࡋࠊᅛయ NMRࡗࡓࠋᅛయ NMRᐃ࡜ᅽ⦰ᙉᗘ

ᐃࢆ⾜ᐃࡣࠊJEOL ECA600ჟ ࡟࡚ 3.2 mm ᅛయࣉ࣮ࣟࣈࢆ౑⏝ࡋࠊMAS ㏿ᗘࡣ෾⤖஝⇱య 10 kHz, ࢤࣝ 4 kHz ࡜ࡋࡓࠋ෾⤖஝⇱యࡣ13C CPMASࡓࠋࢤࣝࡣ㐠ືᛶࡢప࠸ᡂศࢆ

13ᐃ࡟ࡼࡾ஧ḟᵓ㐀ࢆホ౯ࡋᐃࠊ㐠ືᛶࡢ㧗࠸ᡂศࢆ 13C r-INEPTC CPMASᐃ࡟࡚ほࡋࡓࠋResults & Discussion ྛ RSP ࢤࣝࡢ Ala 㐃㙐㡿ᇦࡢ஧ḟᵓ㐀ࡢ๭ྜࢆᐃ㔞ⓗ࡟Ỵᐃࡍࡿࡓࡵ࡟ࢤࣝ
ࡢ෾⤖஝⇱యࡢᅛయ 13C CPMAS NMRᐃࢆ⾜ࡗࡓ㸦Fig. 2㸧ࠋAla Cȕ ࡢࣆ࣮ࢡࢆἼᙧศ㞳ࡋࠊ✚ศᙉᗘẚ࠿ࡽྛ஧ḟᵓ㐀ࡢ๭ྜࢆ⟬ฟࡋࡓࠋȕ-RSPࢤࣝ ࡣ
Ala ṧᇶࡢ 80㸣௨ୖࡀ ȕ-sheet ᵓ㐀ࠊrc-RSP ࡣ45㸣ࡀ random coil ᵓ㐀ࠊĮRSP ࡣ15㸣ࡀ Į-helix ᵓ㐀ࢆ᭷ࡋ࡚࠸
ࡓࠋࢤࣝࡢ 13C CPMAS ࠾ࡼࡧ 13C rINEPT NMRᐃ࡟ࡼࡾࠊྛࢤࣝ୰࡛஧

ḟᵓ㐀ࢆ⥔ᣢࡋ࡚࠸ࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋ ྛ ࢤࣝࡢ◚᩿ᙉᗘ࣭ࡦࡎࡳࣉࣟࢵࢺࠊ
࠾ࡼࡧ௦⾲ⓗ࡞ᛂຊ㸫ࡦࡎࡳ᭤⥺ࢆ Fig.

Fig. 2. 13C CPMAS NMR spectra of freeze-dried rcRSP, Į-RSP and ȕ-RSP gel.

3 ࡟♧ࡍࠋrc-RSP ࢤࣝ࡟ẚ࡭࡚Į-RSP ࢤࣝ࡜ ȕ-RSP ࢤࣝࡢᙎᛶ⋡ࡀ㧗࠿ࡗࡓࠋࡲ
ࡓࠊᛂຊ㸫ࡦࡎࡳ᭤⥺࡟࠾࠸࡚ Į-RSP ࢤࣝ࡟ࡣୗ㝆అⅬࡀᏑᅾࡋ࡚࠾ࡾࠊ Į-RSPࢤࣝ࡜ ȕ-RSP ࢤ࡛ࣝࡣ㧗ᙎᛶ⋡ࡢ࣓࢝ࢽࢬ࣒ࡀ␗࡞ࡿྍ⬟ᛶࡀ♧၀ࡉࢀࡓࠋ ࡇࢀࡽࡢ⤖ᯝ࠿ࡽࠊrc-RSP ࢤࣝࡣ ᯫ
ᶫⅬࡀᑡ࡞࠸ࡓࡵᙎᛶ⋡ࡀపࡃࠊȕ-RSPࢤࣝࡣ ȕ-sheet ᵓ㐀࠿ࡽ࡞ࡿᯫᶫⅬࡀከ࠸ࡓࡵᙎᛶ⋡ࡀ㧗ࡃࠊ Į-RSP ࢤࣝࡣ Įhelix ᵓ㐀࡟ࡼࡾศᏊ㙐ࡀ๛┤࡞ࡓࡵᙎᛶ⋡ࡀ㧗࠸࡜⪃ᐹ࡛ࡁࡿࠋ
Fig. 3. Plots of breaking strength and strain and stress
Referencesvs.

strain[1] Y. Tasei et al., Macromolecules 50,

measurement of rc-RSP gel, Į-RSP gel㸪and ȕ-RSP gel.

8117-8128 (2017).

－ 331 －

curvesofcompression

strengthP89ʌࣃࣝࢫࢺࣞ࢖ࣥࢆ⏝࠸ࡓ㧗㏿MASୗ࡛ࡢᐃᡭἲࡢ㛤Ⓨ

13C-13C DARR‫ۑ‬ᯇỌ㐩ᘺ㸪▼஭ె㄃1,2
1⌮໬Ꮫ◊✲ᡤ⏕࿨ᶵ⬟⛉Ꮫࢭࣥࢱ࣮࣭ඛ➃NMR㛤Ⓨᛂ⏝◊✲ࢳ࣮࣒2ᮾிᕤᴗ኱Ꮫ࣭⏕࿨⌮ᕤᏛ㝔

Development of 13C-13C DARR measurement on fast MAS driven by ʌ-pulse train‫ۑ‬Tatsuya Matsunaga1, Yoshitaka Ishii1,2
1

Laboratory for Advanced NMR Application and Development,
RIKEN Center for Biosystems Dynamics Research

2

School of Life Science and Technology, Tokyo Institute of Technology
Dipolar-Assisted Rotational Resonance (DARR) is one of powerful tools to measure 13C-13C dipolarinteraction in various range on Magic-Angle Spinning (MAS). However, it requires long RF irradiation
whose intensity equals to MAS frequency. Thus, it’s mainly used on as fast as 10–30 kHz MAS and rarely
used on fast/ultrafast MAS with faster spinning than it. In this study, I show 1H-13C dipolar recoupling with
ʌ-pulse train with interval of 1.5-times MAS period. It realized long and low-power recoupling and drove
13C-13C recoupling like DARR, which I call as ʌ-pulse driven DARR (ʌ-DARR). I show that it works on

ultrafast MAS with rotor frequency of 60 kHz.
ᅛయNMR࡟ࡼࡿศᏊෆ࣭ศᏊ㛫ࡢ☢Ẽ┦஫స⏝ࡢ ᐃࡣࡑࢀࡽࡢ㊥㞳᝟ሗࢆࡶࡓࡽࡋࠊ⏕యศᏊࡸ㧗ศᏊࢆࡣࡌࡵ࡜ࡍࡿᵝࠎ࡞≀㉁ࡢᵓ㐀ゎᯒ࡟㈉⊩ࡋ࡚ࡁࡓࠋ୍᪉࡛ࠊࡇࢀࡽࡢ☢Ẽ┦஫స⏝ࡣᅛయNMRࢫ࣌ࢡࢺࣝࡀᗈᖜ໬ࡍࡿཎᅉ࡛ࡶ࠶ࡾࠊᅛయヨᩱࢆ☢ሙ୰࡛㧗㏿ᅇ㌿ࡉࡏࡿ
Magic-Angle Spinning (MAS)ࡸࠊ㠀ほ ᰾࡬ࡢRF↷ᑕ࡟ࡼࡿdipolar decoupling࡞࡝ࠊ☢Ẽ┦஫స⏝ࢆᡴࡕᾘࡍࡇ࡜࡛ࢫ࣌ࢡࢺࣝࢆඛ㗦໬ࡍࡿᡭἲࡀᩘከࡃ
㛤Ⓨࡉࢀ࡚ࡁࡓࠋᅛయNMRⓎᒎࡢṔྐࡣࠊ☢Ẽ┦஫స⏝ࡢdecouple/recoupleࡢᡭἲⓎᒎࡢṔྐ࡛ࡶ࠶ࡿࠋ
Dipolar-Assisted Rotational Resonance (DARR)[1] ࡣᅛయ
MAS NMR࡛ᗈࡃ⏝࠸ࡽࢀࡿྠ✀᰾㛫┦஫స⏝recouplingᡭἲࡢ୍ࡘ࡛࠶ࡿࠋDARR ᐃ࡛ࡣࠊMASࡢヨᩱᅇ㌿㏿ᗘȦr/2ʌ࡜➼ࡋ࠸1H☢໬ᅇ㌿ࢆࡶࡓࡽࡍRFࣃࣝࢫࢆ↷ᑕࡋࠊᩘ༑࠿ࡽᩘⓒms࡜࠸࠺ẚ㍑ⓗ㛗᫬㛫ࡢ1H-13C㛫
dipolar recouplingࢆ㉳ࡇࡍࠋࡇࡢ1H-13C㛫dipolar┦஫స⏝ࢆ௓ࡍࡿ஦࡛㏆㊥㞳࠿ࡽ㐲㊥㞳ࡲ࡛ᗈ࠸⠊ᅖࡢ13C-13C┦
㛵ࢆ ᐃࡍࡿࠋࡋ࠿ࡋࠊ㏆ᖺࡢ50㹼60 kHzࢆ㉸࠼ࡿࡼ࠺࡞㧗㏿/㉸㧗㏿MASୗ࡛ࡣࠊᙉຊ࠿ࡘ㛗᫬㛫ࡢ1H RF↷ᑕࡀᚲせ࡞ࡓࡵࠊDARRࡢ౑⏝ࡀᅔ㞴࡛࠶ࡿࠋᮏ◊✲࡛ࡣࠊ୍ᐃᙉᗘࡢRF↷ᑕ (constant wave, CW)

Fig. 3. 13C CPMAS spectra of 13C,15N-

ࡢ௦ࢃࡾ࡟ࠊʌࣃࣝࢫࡢ⧞ࡾ㏉ࡋࢆ࣮࣋ࢫ࡟ࡋࡓ1H-13C㛫

labeled L-alanine measured with repetition

dipolar recouplingࣃࣝࢫࢆ౑࠺஦࡛㟁ຊࢆᢚ࠼ࠊ60 kHz

of 1H ʌ-pulse with intensity of 30 kHz.

௨ୖࡢMASୗ࡛DARRࡢᵝ࡞13C-13C┦㛵ࢫ࣌ࢡࢺࣝࢆ

MAS frequency is 60 kHz. Periods of the ʌ-ྠ✀᰾㛫┦஫స⏝ࠊ㉸㧗㏿MASࠊᅛయNMR

pulse train are 25.2 ȝs (solid line) and 34.1 ȝs‫ࡸࡘࡓࡀ࡞ࡘࡲۑ‬, ࠸ࡋ࠸ࡼࡋࡓ࠿

(dashed line).

－ 332 －

ᐃࡍࡿᡭἲࢆ㛤Ⓨࡋࡓࠋࡇࡢᡭἲࢆ ʌ-pulse driven
DARR (ʌ-DARR)࡜࿧ࡪ஦࡜ࡍࡿࠋ
Fig. 1 ࡣࠊ60 kHz ࡢ MAS ୗ࡛ࠊᙉᗘ 30 kHz ࡢ 1H ʌࣃࣝࢫࢆ࿘ᮇ Ĳ = 25 ȝs (solid), 34 ȝs (dashed)࡛⧞ࡾ㏉ࡋ࡞ࡀࡽ ᐃࡋࡓ 13C,15N-labeled L-Alanine ࡢ 13C CPMASࢫ࣌ࢡࢺ࡛ࣝ࠶ࡿࠋMAS ࡢᅇ㌿࿘ᮇࡣ Ĳr = 16.67 ȝs ࡛࠶ࡾࠊʌ ࣃࣝࢫࡢ࿘ᮇࡀ Ĳ = 25 ȝs = 1.5Ĳr ࡢ᫬ࡣࣃࣝࢫ
ࡀ 1H recoupling ࡜ࡋ࡚ࠊĲ = 34 ȝs Ң 2Ĳr ࡢ᫬ࡣ 1H
decoupling ࡜ࡋ࡚ാࡃࠋFig. 2 ࡣ ʌ ࣃࣝࢫࡢ࿘ᮇ࡟ࡼࡿ
13CĮ ࣆ࣮ࢡᙉᗘኚ໬ࡢࢢࣛࣇ࡛࠶ࡾࠊĲ ࡟ࡼࡗ࡚ ʌ ࣃࣝࢫࡀ decouple ᮲௳࡜ recouple ᮲௳ࢆ⾜ࡁ᮶ࡋ࡚࠸ࡿ
ࡢࡀศ࠿ࡿࠋRecouple ຠ⋡ࡣ Ĳ = 25, 42 ȝsࠊࡘࡲࡾ Ĳ ࡀ
MAS ࿘ᮇ Ĳr ࡢ༙ᩚᩘಸࡢ᫬࡟᭱኱࡜࡞ࡿࠋࡑࡢ௚ࡢ❑Fig. 2. Dependence of 13CĮ-peak intensity on ʌ-ࡳࡣ MAS ࿘ᮇ࠿ࡽ 1/4 ࿘ᮇࡎࢀࡓⅬ࡛ࠊࡇࡇࡶᙅ࠸

pulse period Ĳ.

recouple ᮲௳ࢆᣢࡘࠋ

Sample was 13C,15N-labeled L-alanine and it was ᙉ࠸ RF ↷ᑕ࡟ࡼࡗ࡚Ⓨ⏕ࡍࡿ㟁ຊࡣࢧࣥࣉࣝࡢຍ

measured with 13C CPMAS on 60 kHz MAS.

⇕ࡸ㟁Ẽᅇ㊰ࡢᦆയࢆᘬࡁ㉳ࡇࡍࡓࡵࠊNMR

Intensity was normalized with the highest pointᐃ࡛ࡣRF ↷ᑕࡢᙉᗘࡸ᫬㛫࡟ὀពࡀᚲせ࡛࠶ࡿࠋʌ-DARR ࡢ

on Ĳ = 34.1 ȝs.

฼Ⅼࡣࠊmixing ᫬ࡢ RF ᙉᗘ࡜↷ᑕ᫬㛫ࢆῶࡽࡏࡿ஦
࡟ຍ࠼ࠊ㧗㏿ MAS ≉᭷ࡢᙅ࠸ 1H decoupling ࣃࣝࢫࡀ౑
࠼ࡿ஦࡛࠶ࡿ>@ࠋ௒ᅇࠊʌ-DARR ࡛⏝࠸ࡿ ʌ ࣃࣝࢫᙉᗘ
ࢆ MAS ࿘Ἴᩘࡢ༙ศ࡜ࡋࡓࠋࡇࡢሙྜࠊmixing ୰ࡢ㟁ຊࡣ㏻ᖖࡢ DARR ࡛౑ࢃࢀࡿ CW ↷ᑕࡢ⣙ 1/6 ࡜࡞ࡿࠋࡲࡓࠊ30 kHz MAS ୗ࡛ࡣ FID ほ ᫬ࡸ㛫᥋ḟඖࡢᒎ㛤᫬㛫࡟ 100 kHz ㏆࠸ᙉᗘࡢ 1H decoupling ࣃࣝࢫࡀᚲせ࡛࠶ࡿࡢ࡟ᑐࡋࠊ60 kHz MAS ୗ࡛ࡣ 10 kHz ⛬ᗘࡢ 1H
decoupling ᙉᗘ࡛༑ศ࡛࠶ࡿࠋFID ࡢ㛗ࡉࢆ 10 ms ࡜ࡋࡓሙྜࠊ60 kHz MAS ࡛ࡢ ʌ-DARR
MAS ࡛ࡢ DARRᐃ࡛࠶ࢀࡤ 30 kHzᐃ࡜ྠ➼ࡢ㟁ຊ࡛ 2–4 ಸࡢ㛗ࡉࡢ

mixing ࢆ⾜࠺஦ࡀ࡛ࡁࡿࠋʌ-DARR ࡢ recouple ຠ⋡ࡣ᭱኱࡛ DARR ࡢ recouple ຠ⋡ࡢ 2/3 ࡛࠶ࡿ஦ࢆຍ࿡ࡋ࡚ࡶ
༑ศ࡟㟁ຊࢆᢚไ࡛ࡁࡿࠋFig. 3 ࡣ 60 kHz MAS ୗ࡛

Fig. 3. 13C-13C ʌ-DARR spectra of 13C,15N-

ᐃࡋࡓ GB1 ࢱࣥࣃࢡࡢ 13C-13C ʌ-DARR ࢫ࣌ࢡࢺ࡛ࣝ࠶

labeled GB1 protein.

ࡿࠋ⧞ࡾ㏉ࡋ᫬㛫ࡀ 2.5 s ࡛࠶ࡾ࡞ࡀࡽ 285 ms ࡶࡢ㛗࠸It was measured on 60 kHz MAS and withmixing ࢆᏳ඲࡟⾜࠺஦ࡀ࡛ࡁࡓࠋ

repetition time of 2.5 s. Mixing was done withcombination of 30 kHz ʌ pulses and 10 kHz

References

decoupling pulses. Mixing time was 285 ms.

[1] K. Takegoshi et al., (2001) 13C-1H dipolar-assisted rotational
resonance in magic-angle spinning NMR, Chem. Phys. Lett. 344 631–637.
[2] M. Ernst et al., (2001) Low-power decoupling in fast magic-angle spinning NMR, Chem. Phys. Lett. 348 293–302.
A. Wickramasinghe et al., (2015) Evolution of CPMAS under fast magic-angle-spinning at 100 kHz and beyond, SSNMR
72 9–16.㻌

－ 333 －

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ࣇࢵ⣲໬ࢫࣝ࣍ࣥ㓟࢔࢖࢜ࣀ࣐࣮ศᩓᾮࡢ㧗㏿☢ሙࢧ࢖ࢡࣜࣥࢢNMR ᐃ‫ۑ‬ᒣཱྀ┿㸪ᑎᑿ๛ᢏ⾡◊✲⤌ྜFC-Cubic

Fast Field-Cycling NMR Relaxometry of Perfluorosulfonic Acid Ionomer Dispersions‫ۑ‬Makoto Yamaguchi, Takeshi Terao
Fuel Cell Cutting-edge Research Center (FC-Cubic)
Spin-lattice relaxation rate of perfluorosulfonic acid (PFSA) ionomer dispersions in polar solvents were
measured by field-cycling relaxometry. Contributions of local motions (defect diffusion along main chain),collective order fluctuations, and rotational diffusion of the dispersed particles are supposed to be
responsible to explain frequency dependence, which basically obeys power law with changing indices.
ࢼࣇ࢕࢜ࣥ࡞࡝ࡢࣇࢵ⣲໬ࢫࣝ࣍ࣥ㓟(Perfluorosulfonicacid:PFSA)࢔࢖࢜ࣀ࣐࣮ࡣ㸪ᅛయ㧗ศᏊᙧ⇞ᩱ㟁ụࡢࣉࣟࢺࣥఏᑟ⭷ࡸゐ፹ᒙ࡟⏝࠸ࡽࢀ࡚࠸ࡿࠋࡇࢀࡽࡣᴟᛶ⁐፹ࡢศᩓᾮ࡜ࡋ࡚ᥦ౪ࡉࢀ࡚࠾ࡾ㸪ศᩓ⢏Ꮚࡢࢧ࢖ࢬࡸᙧ≧ࡸ㐠ືᛶࡀ〇ရࡢㅖ≉ᛶࢆᕥྑࡍࡿ㸬ᡃࠎࡣ㧗㏿☢ሙࢧ࢖ࢡ
ࣜࣥࢢ(Fast Field-Cycling : FFC) NMRࡢ㐺⏝ྍ⬟ᛶࢆ᳨ウࡋ㸪ࢫࣆࣥ᱁Ꮚ⦆࿴㏿ᗘࡢ࿘Ἴᩘ౫ᏑᛶࢆศᏊ㙐ୖࡢḞ㝗ᣑᩓ࠾ࡼࡧ⢏Ꮚࡢᅇ㌿ᣑᩓ࡛ㄝ᫂ࢆヨࡳ࡚ࡁࡓࡀ(1)㸪௒ᅇࡣ⭷ヨᩱࡢ ᐃ⤖ᯝ࡜ࡢẚ㍑࠿ࡽศᏊ㙐ࡢ㞟ᅋ㐠ືࡢᐤ୚ࡶྵࡵ࡚⪃ᐹࡋࡓ㸬
ᐃ⿦⨨ࡣSpinmaster2000(Stelar S.r.l., Italy)ࢆ⏝࠸ࡓ㸬ࡇ

Fig. 1. FFC-NMR measurementࡢ⿦⨨ࡣ㟁☢▼࡟ࡼࡿ☢ሙᙉᗘࢆ㧗㏿࡛ษ᭰ࡀྍ⬟࡛࠶ࡿ㸬 ᐃἲࢆFig.1࡟♧ࡍ㸬ศᴟ☢ሙ(19F᰾࣮ࣛࣔ࢔࿘Ἴᩘ

CF 2

m

27.5MHz)࡛ヨᩱࡢ⦪☢໬ࢆ⏕ᡂࡋ㸪⦆࿴☢ሙ(0.005-40MHz)

CF
O
F 2C

ࢆษࡾ᭰࠼࡚☢໬ࢆ⦆࿴ࡉࡏ㸪୍ᐃ᫬㛫⤒㐣ᚋࡢ☢໬ࢆ᳨ฟ☢ሙ(17MHz)࡛FID᳨ฟࡍࡿ㸬⦆࿴☢ሙࡢ༳ຍ᫬㛫ࢆኚ࠼

CF 2

CF 2

CF 2 SO 3H

Fig. 2. Structure of Aquivion࡚ ᐃࢆ⧞ࡾ㏉ࡋ㸪FIDಙྕᙉᗘࢆᣦᩘ㛵ᩘ࡛ࣇ࢕ࢵࢺࡋT1ࢆồࡵࡿ㸬ࡇࢀࢆ⦆࿴☢ሙᙉᗘࢆኚ࠼࡚ࢫࣆࣥ᱁Ꮚ⦆࿴㏿ᗘ(R1=1/T1)ࡢ࿘Ἴᩘࣉࣟࣇ࢓࢖ࣝࢆᚓ
ࡿ㸬௒ᅇࡣᙜ㔞㔜㔞(EW)ࡢ␗࡞ࡿᕷ㈍ရࡀධᡭྍ⬟࡞▷ഃ㙐ᆺ࢔࢖࢜ࣀ࣐࣮(Aquivion㸪Fig.2)ࡢ
Ỉศᩓᾮ࠾ࡼࡧ⭷ࢆ⏝࠸㸪㛗ഃ㙐ᆺࡢ ᐃ⤖ᯝ࡜ẚ㍑ࡋࡓ㸬EW790ࡢỈศᩓᾮ(D79-25BS㸪25wt㸣)࡜⭷(E79-12S㸪⭷ཌ120m)ࡢࢫࣆࣥ᱁Ꮚ⦆࿴㏿ᗘࣉࣟࣇ࢓࢖ࣝࢆFig.3࡟♧ࡍ㸬ప࿘Ἴᩘഃࡣศᩓᾮ࡛ࡣ5kHzࡲ࡛ ᐃ࡛ࡁࡓࡀ㸪⭷࡛ࡣFIDࡢῶ⾶ࡀ㏿ࡃ
0.2MHzࡀୗ㝈࡛࠶ࡗࡓ㸬10MHz௨ୖ࡛ࡣ ᗘ࠾ࡼࡧヨᩱᙧ≧ࡢᙳ㡪ࡀ࡞ࡃ㸪ᣦᩘ-1ࡢ࡭ࡁ஌࡛
㏆ఝ࡛ࡁࡿ㸬ࡇࡢ㡿ᇦࡣ㛗ഃ㙐ᆺ࢔࢖࢜ࣀ࣐࣮ࡢỈศᩓᾮ࡛ࡶほ ࡉࢀࡓࡀ㸪㛗ഃ㙐ᆺ࡛ࡣ⣙
15MHz௨ୖ࡛ほᐹࡉࢀࡓᣦᩘ-3/2ࡢ㡿ᇦ(1)ࡀㄆࡵࡽࢀ࡞࠿ࡗࡓ㸬⇞ᩱ㟁ụ㸪㧗ศᏊ㸪ࢫࣆࣥ᱁Ꮚ⦆࿴
‫࡜ࡇࡲࡕࡄࡲࡸۑ‬㸪࡚ࡽ࠾ࡓࡅࡋ

－ 338 －

୍᪉㸪0.2MHz௨ୗ࡛ࡣศᩓᾮࡢ⦆࿴㏿ᗘࡣ࡯ࡰ୍ᐃ࡜࡞ࡾ㸪 ᗘࡀ㧗࠸࡯࡝⦆࿴㏿ᗘࡣపୗࡋࡓ㸬PFSA࢔࢖࢜ࣀ࣐࣮ࡢỈศᩓᾮ࡛ࡣᩘnmࡢኴࡉࡢᲬ≧⢏Ꮚࡀศᩓࡋ࡚࠾ࡾ(2)㸪⢏Ꮚ඲యࡢᅇ㌿ᣑᩓ࡟ࡼࡿᐤ୚ࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡿ㸬
10㹼0.2MHzࡢ㡿ᇦ࡛ࡣప࿘Ἴᩘഃ࡟࠿ࡅ࡚
ᐃⅬࡢഴࡁࡀᣦᩘ-1࠿ࡽḟ➨࡟⦆ࡸ࠿࡟࡞ࡗࡓ
ࡀ㸪0.2MHz௜㏆࡛ࡢഴࡁࡣ303K࡛ࡣᣦᩘ-3/4⛬ᗘ࡛࠶ࡗࡓࡶࡢࡀ353K࡛ࡣ⣙-1/2࡟ࡲ࡛ኚ໬ࡋࡓ㸬ࡇࡢᣲືࡣศᩓᾮ࡜⭷ࡢ཮᪉࡛ㄆࡵࡽࢀࡓࡀ㸪
353Kࡢ⭷࡛ࡣ10㹼0.2MHzࡢ඲ᇦ࡛ᣦᩘ-1/2ࢆ♧ࡋࡓ㸬ࢫࣆࣥ᱁Ꮚ⦆࿴࿘Ἴᩘࣉࣟࣇ࢓࢖ࣝࡀ࡭ࡁ஌๎
࡟ᚑ࠺౛ࡣ㧗ศᏊࡸᾮᬗ࡞࡝࡛ከࡃሗ࿌ࡉࢀ㸪ྠ

Fig. 3. Relaxation dispersion of Aquivion(EW=790)ࡌ࡭ࡁ஌๎࡟ᑐࡋ࡚ࡶ␗࡞ࡿࣔࢹࣝ࡟ࡼࡿㄝ᫂ࡀ
࡞ࡉࢀ࡚࠾ࡾ㸪ᐇ㦂⤖ᯝࡢ୍ពⓗ࡞ゎ㔘ࡣ㞴ࡋ࠸(3)㸬㞀ቨ㛫ࡢ᭷㝈⠊ᅖࡢḞ㝗ᣑᩓ࡟ࡼࡿ⦆࿴ᶵᵓ
࡟ࡼࢀࡤ㸪࡭ࡁ஌ࡢᣦᩘࡀ㧗࿘Ἴᩘഃ࠿ࡽ-3/2Ѝ-1/2Ѝ0࡜ኚ໬ࡍࡿ࡜ண

ࡉࢀࡿ(4)㸬PFSA࢔࢖࢜ࣀ࣐࣮ࡣPTFE࡜ྠᵝࡢ୺㙐ᵓ㐀ࢆ᭷ࡋ㸪PTFE࡛ほᐹࡉࢀࡿ஧㔜ࡽࡏࢇ཯㌿࡜㢮ఝࡢḞ㝗ࡀ୺㙐ୖࢆᣑᩓࡋ㸪ഃ㙐ࡢᏑᅾࡀᣑᩓ㞀ቨ࡜࡞ࡿ࡜⪃࠼ࡽࢀࡿࡇ࡜࠿ࡽ㸪௨๓ࡢⓎ⾲࡛ࡣࡇࡢࣔࢹࣝࡀ
㐺⏝ྍ⬟࡜⪃࠼ࡓ(1)㸬Lenkࡣ㧗࿘Ἴᩘഃࡢᣦᩘ-3/2࡜ప࿘Ἴᩘഃࡢᣦᩘ-1/2ࢆྵࡴ୍⯡໬ࡉࢀࡓࢫ
࣌ࢡࢺࣝᐦᗘ㛵ᩘࢆᥦ᱌ࡋࡓࡀ(5)㸪ࡇࢀ࡟ࡼࢀࡤ୧⪅ࡢ୰㛫㡿ᇦ࡛ᣦᩘ-1࡜࡞ࡾ㸪⦆࿴㏿ᗘࡢ ᗘ౫Ꮡᛶࡢᾘኻࡶྠ᫬࡟ㄝ᫂ྍ⬟࡛࠶ࡿ㸬୍᪉㸪353Kࡢ⭷࡛ᗈ࠸㡿ᇦ࡛⣙-1/2ࡢ࡭ࡁ஌ࡀほࡉࢀࡓࡀ㸪ࢿ࣐ࢸ࢕ࢵࢡᾮᬗࡢ㓄ྥࡺࡽࡂ࡟㉳ᅉࡍࡿ࿘Ἴᩘ౫Ꮡᛶࡶᣦᩘ-1/2ࢆ♧ࡍࡇ࡜ࡀ▱ࡽࢀ࡚࠾ࡾ㸪ᾮᬗᛶ࣏࣐࣮࡛ࣜࡣᣦᩘࡀ-0.65࡜࡞ࡿ⤖ᯝࡀሗ࿌ࡉࢀ࡚࠸ࡿ(6)㸬PFSA࢔࢖࢜ࣀ࣐࣮ࡣ୺㙐㦵᱁ࡢᖹ⾜㓄ิ࡟⏤᮶ࡍࡿX⥺ᅇᢡࣆ࣮ࢡࢆ1.2nm-1௜㏆࡟♧ࡍࡀ㸪ࡇࢀࡣ⭷ࡔࡅ࡛࡞ࡃศᩓᾮ࡛ࡶほᐹࡉࢀࡿࡇ࡜࠿ࡽ㸪ᣦᩘ-1/2ࡣ୺㙐㓄ิࡢ㞟ྜⓗ⛛ᗎࡢࡺࡽࡂ࡟㉳ᅉࡍࡿࢫࣆࣥ᱁Ꮚ⦆࿴࡟㉳ᅉࡋ࡚࠸ࡿྍ⬟ᛶࡶ⪃࠼ࡽࢀࡿ㸬ࡇࡢሙྜࡣ㞟ྜⓗ⛛ᗎࡢ┦㛵㛗࡟ᑐᛂࡋ࡚࿘Ἴᩘࡢపୗ࡟క࠸ᣦ
ᩘࡀ-1/2࠿ࡽ0࡬࡜⛣⾜ࡍࡿ࡜⪃࠼ࡽࢀࡿ㸬
ᮏⓎ⾲ෆᐜࡣ᪂࢚ࢿࣝࢠ࣮࣭⏘ᴗᢏ⾡⥲ྜ㛤Ⓨᶵᵓࡢࠗ⇞ᩱ㟁ụ➼฼⏝ࡢ㣕㌍ⓗᣑ኱࡟ྥࡅࡓ
ඹ㏻ㄢ㢟ゎỴᆺ⏘Ꮫᐁ◊✲㛤Ⓨ஦ᴗ࠘࡟ࡼࡿᡂᯝࡢ୍㒊࡛࠶ࡿ㸬
References(1) ᒣཱྀ┿ (2019) 㧗㏿☢ሙࢧ࢖ࢡࣜࣥࢢ NMR ࡟ࡼࡿỈ⣔ศᩓᾮ୰ࡢࢼࣇ࢕࢜ࣥ⢏ᏊࡢศᏊ㐠ືᛶࡢ᳨ウ㸪➨ 68 ᅇ㧗ศᏊウㄽ఍. (2) Yamaguchi, M., Terao, T., Ohira, A., Hasegawa, N., Shinohara, K.
(2019) Size and shape of Nafion particles in water after high-temperature treatment. J. Polym. Sci. B 57, 813818. (3) Kimmich, R. (2012) Principles of Soft-Matter Dynamics. (4) Kimmich, R., Voigt, G. (1978) DefectDiffusion Models in NMR and Dielectric Relaxation. Z. Naturforsch. 88a, 1294-1306. (5) Lenk, R. (1975)
Diffusion and spin relaxation. Adv. Molec. Relaxation Process. 6, 287-306. (6) Zeuner, U., Dippel, T. Noack, F.,
Mueller, K., Mayer, C., Heaton, N., Kothe, G. (1992) Proton spin-lattice relaxation dispersion of liquid crystal
polymers: Characterization of local and collective motions. J. Chem. Phys. 97, 3794-3802.

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P92Y

Perdeuterated Į-helical membrane protein preparation methods for
proton detection MAS solid-state NMR
Xin Zhang1, Hajime Tamaki1, Toshimichi Fujiwara1,2
1

Institute for Protein Research, Osaka University

2

Center for Quantum Information and Quantum Biology Division, Institute forOpen and Transdisciplinary Research Initiatives, Osaka University

Perdeuteration improves the sensitivity and resolution of solid-state NMR by suppressing magnetic
interactions with protons, which makes it a suitable method for measuring membrane protein complex
structural information under physiological condition. However, it is difficult to re-introduce 1H to Į-helicalmembrane proteins for ssNMR detection. In this study, we prepared perdeuterated Natronomonas pharaonis
halorhodopsin (NpHR), a membrane protein with 7 Į- helices via several methods. The H/D exchanging
efficiency and sample quality were evaluated by proton detection ssNMR measurements under 70 kHz magic
angle spinning with a 700 MHz spectrometer and will be discussed in this presentation.
Structural studies for membrane proteins are important because those proteins play important roles inphysiological activities. Solid-state NMR (ssNMR) is a suitable method for membrane proteins structural
analysis because it provides not only structural information but also molecular dynamic information at atomic
level under physiological condition. Compared with commonly used 13C and 15N detection ssNMR, 1H
detection ssNMR provides better sensitivity and resolution. However, the strong 1H-1H dipolar interaction
results in a homogeneous line-broadening and limits the spectral resolution. The state-of-art ssNMR
instrument enabled magic angle spinning (MAS) frequency towards 150 kHz with magnet field up to 1.2
GHz (28 T) which provides narrower proton linewidth. However, even under those conditions dipolarinteraction contributes to a major part in line-broadening1; about 100 Hz homogeneous broadening remainedin fully protonated protein samples2. Deuteration still benefits to spectral resolution and signal sensitivity andenables ssNMR measurement to larger membrane protein complexes.
Perdeuteration and proton back exchange is a commonly used method to prepare 2H with 1HN labeledprotein for backbone structural and dynamic analysis with ssNMR. Perdeuterated proteins can be expressedin E. coli with D2O based media and re-introducing 1HN via proton back exchange in aqueous solution.
However, the application of this method to Į-helical membrane proteins faces difficulties. The protein folded
structure and the hydrophobic surrounding environment prevent the 2HN exchanging with solvent 1H2O andcause heavily signal losses3. Denaturing the proteins can increase the water accessibility and improve protonback exchange ratio. However, finding the refolding condition for Į-helical membrane proteins is difficult.
Limited works were focused on preparing 2H with 1HN labeled Į-helical membrane proteins throughperdeuterated samples via unfolding and refolding protocol. A cell free expression system can be a better
choice for 2H with 1HN labeled Į-helical membrane protein preparation by using 2H, 13C and 15N labeledamino acids. In cell free expression system, protein is synthesized using cellular extraction in 1H2O based
reaction buffer via free amino acids molecules. Theoretically, the proton back exchange already happened inamide acid molecules before protein synthesis thus the signal losses related to incomplete proton backMAS solid-state NMR, perdeuteration membrane protein－ 340 －

exchange can be totally avoided. However, cell free synthesis method also has problems. The chemical
environment differences between living cells and reaction buffer may affect the protein structure; unwanted
amino acid metabolic pathways may remain in cellular extraction and introduce additional 1H to proteins byscrambling. Therefore, it is necessary to evaluate sample preparation method before formal structural study.
In this study, 2H with 1HN, 13C and 15N labeled NpHR sample was prepared through E. coli expression andcell free synthesis and evaluated by ssNMR.
Perdeuterated with 13C and 15N labeled NpHR was expressed by E. coli with D2O based M9 medium
and proton back exchanged in native state or SDS denatured condition. A novel dialysis method is developed
for SDS removal and NpHR refolding using DMPC/CHAPS mixture. Cell free synthesized 2H with 1HN, 13C
and 15N labeled NpHR was prepared by a commercial kit from Taiyo-Nippon-Sanso. NpHR samples were
purified by Ni-affinity chromatography and reconstituted in DMPC liposome for ssNMR measurement. The
ssNMR measurements in this study were performed with a JEOL 700 MHz (16.4 T) spectrometer under 70
kHz MAS. Probe temperature was set to -40 ႏ where sample temperature was approximately at 20 ႏ.

Fig. 1 1H-15N HSQC spectra of 2H with 1HN, 13C and 15N labeled NpHR by E. coli expression(left) and cell free synthesis (right)
2H labeled NpHR provided an average proton linewidth of 200Hz in 1H-15N HSQC spectra (Fig. 1),

which was 30% narrower than that from fully protonated sample. Signal losses related to incomplete protonback exchanging can be observed in E. coli expressed NpHR spectrum even after unfolding and refolding.
While no significant signal losses were observed in cell free synthesized NpHR spectrum. The details ofsample preparation and ssNMR analysis will be discussed in the presentation.
References:(1) Nimerovsky, Evgeny, et al. "Proton detected solid-state NMR of membrane proteins at 28 Tesla (1.2
GHz) and 100 kHz magic-angle spinning." Biomolecules 11.5 (2021): 752.
(2) Schledorn, Maarten, et al. "Protein NMR Spectroscopy at 150 kHz MagicဨAngle Spinning Continues To
Improve Resolution and Mass Sensitivity." ChemBioChem 21.17 (2020): 2540-2548.
(3) Linser, Rasmus, et al. "Protonဨdetected solidဨstate NMR spectroscopy of fibrillar and membraneproteins." Angewandte Chemie International Edition 50.19 (2011): 4508-4512.

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P93

High-dimensional 1H-detected SSNMR for Expeditious
Characterization of Aȕ42 Fibrils
Ayesha Wickramasinghe1, Yiling Xiao2, Yoshitaka Ishii1,2,3
1

RIKEN Center for Biosystems Dynamics Research, RIKEN, Yokohama, Kanagawa,

Japan
2

Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois, USA

3

School of Life Science and Technology, Tokyo Institute of Technology, Yokohama,

Kanagawa, Japan
Among various analytical techniques, solid-state NMR (SSNMR) spectroscopy is the most powerfultool for elucidating the atomic level structures of amyloid-ȕ (AE) and other amyloid fibrils. In this study, weevaluate the applicability of high-dimensional 1H-detected SSNMR under ultra-fast MAS (UFMAS)
integrated with non-uniform sampling (NUS) method for a fully protonated 42-residue AE (AE42) fibril in
nano-mole scale. Our results demonstrate the feasibility of efficient characterization of a ~42 nmol of fully
protonated Aȕ42 fibril using sparsely sampled 4D SSNMR spectral data within a couple of days ofexperimental time.
Fibrillar assemblies of Aȕ fibrils have been a subject of intense research due to their close association
with Alzheimer’s disease (AD).1 Among different AE species present in AD brain, AE42 fibril is consideredas the most pathogenic species since it exhibits notably higher neurotoxicity and aggregation propensity.2
Thus, structural characterization of AE42 fibril is crucial for a profound understanding of the mechanism of
AD. However, due to their insoluble and non-crystalline nature, it has been difficult to characterize AE fibrils
by conventional structural tools such as solution NMR and X-ray crystallography. SSNMR spectroscopy has
been the most powerful analytical technique to determine the atomic level structures of AE fibrils.3-5
Nevertheless, essentially only one unique structure having S-shaped E-sheet arrangement is elucidated byprevious SSNMR studies on AE42 fibrils prepared at a physiological pH.5-7 These SSNMR studies on AE42
fibrils relied on 13C-detected SSNMR, which is effective, but generally requires a large amount of sample(~5-20 mg) to record NMR spectra with sufficient sensitivity. Furthermore, high-dimensional NMR spectra(typically 3D and 4D) are required to achieve sufficient resolution for a reliable resonance assignment, which
subsequently demands prolonged experiment time. However, these requirements, which are often nonviable,
limit practical biological applications. With recent advances, 1H-detected high-dimensional SSNMR cancircumvent the above limitations of conventional SSNMR.8 Additional time saving is attainable by sparsely
sampling data points in indirect dimensions using NUS protocols.
In this study, we evaluate the applicability of 1H-detected 4D SSNMR under UFMAS integrated with
NUS for a fully protonated Aȕ42 fibril in nano-mole scale (~42 nmol or ~200 g). This approach allows one
to extract structural profile of AE42 fibril from 25-100 times less sample amount compared to traditional 13Cdetected SSNMR. Here, we recorded

1H-detected

4D experiments such as (H)CACONH and(H)CA(CO)NCAH with 25% NUS to assign the resonances of the protein-backbone of the AE42 fibril.
Excellent sensitivity of NMR spectra by 1H-detection and dramatic enhancement of 1H resolution by UFMAS
at 90 kHz permitted us to assign 94% of 13CD, 82% of 15N, 67% of 13CO and 1H1, and 76% of 1HD resonancesAE fibrils, 1H-detected SSNMR, Non-uniform sampling－ 342 －

from the structured region of the backbone (Tyr 10-Ala 42) within 2.3 days of experiment time. Other details
will be discussed in the presentation.

References
1. V. H. Finder, J. Alzheimer's Dis. (2010) 22, S5íS19.
2. G. Meisl, X. Yang, E. Hellstrand, B. Frohm, J. B. Kirkegaard, S. I. A. Cohen, C. M. Dobson, S. Linse, T.
P. J. Knowles, Proc. Natl. Acad. Sci. USA (2014) 111 (26), 9384.
3. A.T. Petkova, Y. Ishii, J. J. Balbach, O. N. Antzutkin, R. D. Leapman, F. Delaglio, R. Tycko, Proc. Natl.
Acad. Sci. USA (2002) 99(26), 16742-16747
4. I. Bertini, L. Gonnelli, C. Luchinat, J. Mao, A. Nesi, J. Am. Chem. Soc. (2011) 133(40), 16013-16022
5. Y. Xiao, B. Ma, D. McElheny, S. Parthasarathy, F. Long, M. Hoshi, R. Nussinov, Y. Ishii, Nat. Struct.
Mol. Biol. (2015) 22, 499-505
6. M. T. Colvin, R. Silvers, Q. Z. Ni, T. V. Can, I. Sergeyev, M. Rosay, K. J. Donovan, B. Michael, J. Walls,
S. Linse, R. G. Griffin, J. Am. Chem. Soc. (2016) 138, 9663-9674
7. M. A. Walti, F. Ravotti, H. Arai, C. G. Glabe, J. S. Wall, A. Bockmann, P. Guntert, B. H. Meier, R. Riek,
Proc. Natl. Acad. Sci. USA (2016) 113, E4976-E4984
8. A. Wickramasinghe, Y. Xiao, N. Kobayashi, S. Wang, K. P. Scherpelz, T. Yamazaki, S. C. Mereddith,Y. Ishii, J. Am. Chem. Soc. (2021) 143, 11462–11472.

－ 343 －P94Y

NMR࡟ࡼࡿ㔠ᒓ᭷ᶵᵓ㐀యࡢCO2྾╔ືຊᏛ࡟ᑐࡍࡿ⤖ᬗࢧ࢖ࢬࡢᙳ㡪ࡢ◊✲‫ۑ‬ጧ ೧᫂1㸪Ṋ⏣ ࿴⾜11ி㒔኱Ꮫ ⌮Ꮫ◊✲⛉ ໬ᏛᑓᨷCrystal-size effect on the kinetics of CO2 adsorption in metal organic frameworks
studied by NMR‫ۑ‬Weiming Jiang 1, Kazuyuki Takeda 1
1

Division of Chemistry, Graduate School of Science, Kyoto University
We investigate the kinetics and exchange of carbon dioxide (CO2) adsorbed in a metal organic framework(MOF) with various crystal sizes. The crystal-size dependence of the 13C NMR lineshape of the guest CO2
molecules can be explained by asymmetric exchange between the motion-restricting adsorption sites and thehindrance-free isotropic sites. The trend that the smaller the host crystal are, the faster the exchange is, canbe explained by the surface-to-volume ratio.
Introduction
Metal-organic frameworks (MOFs) are porous materials composed of metal clusters and organic linkers.
The porosity of MOFs offering diverse applications, such as gas storage/separation, catalysis, sensing, andso on, not only rely on the host-guest interactions determined by the chemical structures, but also can becontrolled by the crystal size and thereby the accessibility of the active surface sites. Even though solid-state
NMR works have successfully revealed the dynamics and diffusion of the guest molecules, the particle size
effect has so far been overlooked.
Here, we study the crystal-size dependence of the kinetics
of CO2 adsorbed in [Zn2(1,4-NDC)2(dabco)]n MOF(NDMOF, Fig. 1) with 13C NMR.1
Experimental
We synthesized single crystals of NDMOF, and crushedthem into microcrystals with different sizes. The individual
sample is put into a capillary and evacuated before being
flame-sealed together with 13CO2 with pressure of 90 kPa.
The samples include: 1. cc@CO2 (crushed crystals of
100~200 m in size), 2. pd@CO2 (coarse powder of 10~20
m in size), 3. spd@CO2 (fine powder of 1~2 m in size).
The 13C spectra were measured by a home-built probe in 7 T
at room temperature.

Fig. 1. Structure of [Zn2(NDC)2(dabco)]n
MOF (NDMOF). Hydrogen atoms are
not shown.

Results and Discussion

The 13C spectrum of cc@CO2 showed resonance within a range from 107 to 155 ppm (Fig. 2a), which is
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small compared to that for pure solid CO2 íWR SSP 
indicating that the adsorbed CO2 undergo fast reorientation
causing partial averaging of the chemical shift anisotropy. The
axially symmetric power pattern can be explained by a modelin which the CO2 molecules adsorbed inside the pore of
NDMOF behave as if they gyrate around an axis tilted by 61°
against the c-axis of the host crystal. It should be noted,
however, that the actual dynamics is superposition ofreorientation and translation, the latter of which does not affect
the NMR lineshape.2
Conversely, we observed striking differences in the line
shape of the 13C spectra for pd@CO2 and for spd@CO2(Fig. 2b, 2c). Since the host structure is common for all
samples, the motion of CO2 inside the MOF lattices is
supposed to remain unchanged. Thus, the observed change inthe spectrum as downsizing the particle is ascribed to exchangeof the CO2 molecules from one site to another, driven bydiffusion across the pores, the gas phase, and different,
randomly orientated crystallites. Such multi-site exchange
among the motion-restricting adsorption sites (core site) andthe hindrance-free isotropic sites, as schematically depicted in
Fig 3a, require complicated calculation in lineshape analysis.

Fig. 2. 13C NMR spectra of a) cc@CO2,b) pd@CO2, and c) spd@CO2 obtainedin 7 T (Solid lines: experimental,
broken lines: calculated).

We found that, for 1D NMR lineshape analysis, the multisite exchange can be reduced to isolated exchange between
different core sites and the isotropic sites (Fig. 3b). Based on
this idea, we calculated the lineshape using an asymmetricexchange model with various exchange rates.1
This model successfully reproduced the experimental 13C
spectra of pd@CO2 and spd@CO2 (broken lines in Fig. 2b, 2c)with the rate of exchange from the core to the isotropic sites
k = 200 Hz and the population of the core sites p = 0.628, p =0.115, respectively. Further, the 13C spectrum of pd@CO2

Fig. 3. Schematic diagram of (a) the
multi-site exchange among crystallites
through gaseous phase, (b) the isolated

measured in 14 T and 2D exchange spectroscopy (EXSY)

exchange model. Solid and open boxes

experiments also supported our model.1

represent the core and the isotropic

Summarysites.

The CO2 molecules adsorbed in NDMOF undergo exchange among different crystallites and between theisotropic and the core sites. It is the size dependence of the rate of exchange that affects the size-dependent
NMR lineshape. The particle-size effect that we observed in this work can also be seen in many other MOFguest systems, and therefore needs attention in upcoming NMR investigations.
References
1.

W. Jiang, K. Takeda, Phys. Chem. Chem. Phys., 2022, in press. DOI: 10.1039/D2CP03226K.

2.

L. C. Lin, J. Kim, X. Kong, E. Scott, T. M. McDonald, J. R. Long, J. A. Reimer and B. Smit, Angew. Chem.
Int. Ed., 2013, 52, 4410–4413.

－ 345 －

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333<3<Ίͽ౨ ޻‫ݓ‬3<ࢀౣ ਜ਼‫و‬/3<333<3ඝ૖ ௜ध

3

ਭӿ ཤິ

3

ೖ෨ ༦ଢ

3

ਭ໼ ‫ݫ‬ദ/3333<3ฑඎ ༑Մ

3ਭଞ ୕໷

/߁ੋ ိ

/3ྰ॑ Ի

/኏௣ ௜ध

3

‫ ీٸ‬༡‫ي‬3<኏੤ ྐྵՅ

3<‫ٸ‬੤ ޻Ҳ࿢3<‫ٸ‬ό೘ ༺ฑ///3<΀਄ᖔ ६

3<΋౽ઔ ߝध

/ଞ৏ կਕ

3</౽‫ٍ ރ‬দ3<ଞ৏ ඔ࿪

/౽࿚ ୉ื

/3<౽ଞ ཆ

3<๮݆ ༐‫ن‬3<౽ଞ ླ

3

෼෨ ༲ࢢ/౽‫ ݬ‬࿪෋3<ਁ ষࢢ/౽‫ ݬ‬ෆಕ/ / 3< 3< 3<ਁӮ ཾࢦ

3<33333<ਁຌ ୉ஒ

$//33<3౽‫྇ ݬ‬ฑ3<ঀԮ ౵

3‫ݻ‬൚ ‫ࢢڭ‬/3<3<3໵ీ ఱࢢ

/

΍

Ά

Ώ

੗໼ ਇҲ/ൂඎ ࣐

3

ࡋߒ ࡌʓ՘

3

ൂ໨ ୣ‫ن‬3

ࡋీ ࿪஋

3

ൂ໨ ޼থ

/ࡋీ ௜/҈Ҭ ᰞ

/ຌؔ ಕ෋

/༆ୖ ߠଢ

3<༆ీ ိध

3<ΉṶᔻ ༓࣑

3

Բ෨ ষ୉

3ন໨ ཇ

/3<333ࢃ಼ Ҳ෋

//3<3<3<ন‫ ۿ‬৵໷3<ࢃ஖ ༐୉

/3<নీ ༒

/333ࢃ޳ ऴ߀

3নӮ Ҳଢ

3ࢃ޳ ਇ

3নӮ ୣ໽

/33ࢃ㟔 ଢҲ3

－ 352 －

ࢃ࡜ य़෋

3<33<ࢃీ ൑࢜

33<3ࢃీ ߸࢛

3<ࢃຌ ‫ߵښ‬3

ࢃຌ ߦٍ

33<ࢃຌ ९໷

/3ࢃຌ կ೯

3Γԥઔ ਇཨࢢ

/3<ԥߖ ஒ‫ي‬3/ԥࢃ ࿪࠺

/3<ԥࢃ ୉‫م‬33٤ઔ Ҳิ

3<٤ీ ੜඔ

3<٤ਭ ߁໎

3

٤ଞ ߄৵

3<Κऑন ֞

+/33<ऑຌ ୕࿗

3

ऑࢃ ਜ਼ཾ

3

࿪ీ থ‫ٳ‬/ోᬓ Ҳ໷

/ోᬓ ᰞ

/ోᬔ ӵ޼

3

ోᬔ ཥٍ

3 

－ 353 －

Alphabetical OrderA

Fujimura Haruka

P44Y

Fujimura Rei

P25

Aida Takuzo

P32Y

Fujinami Daisuke

L2-5, P64Y

Aizawa Tomoyasu

L5-1, L5-6, P24Y, P28Y,

Fujito Teruaki

P78Y

P33, P34Y, P52Y

Fujiwara Kazuo

P50Y

Akabane Tatsuki

P23

Fujiwara Ryouhei

P78Y

Akagi Ken-ichi

L4-2

Fujiwara Toshimichi

L1-5, L4-2, P10Y, P14Y,

Akasaka Kazuyuki

P51

P32Y, P35, P45, P61, P77,

Amemori Syogo

P19, P53

P92Y

Amoureux, Jean-Paul

L1-6

Fukazawa Jun

P70Y

Ando Hideka

P76Y

Furuita Kyoko

L4-2, P14Y, P32Y, P61

Ando Takami

P67, P68Y

Aono Keita

P62Y

Aoyama Hiroshi

L2-1, P6Y, P72

Arita Kyohei

P73

Asakawa Naoki

P4Y

Asakura Katsuo

P40Y

Hamaguchi Isao

P1

Asakura Yoshimitsu

P65

Hanaoka Ami

P52YAsano Atsushi

P38Y

Hasegawa Takuya

P6Y

Asao Nobuaki

P66Y

Hashi Kenjiro

P78Y

Ayabe Tokiyoshi

P24Y

Hata Yuki

P20Y

Hattori Yoshikazu

L4-2

B

G
Gan, Li

P24Y, L5-1, L5-6, P28Y,
P33, P34Y

Gotoh Kazuma

P76Y, P78Y
H

Bao Xinnu

P17

Hayashi Fumio

P87

Binder, Wolfgang H.

IL-1

Hayashi Seiichiro

P64Y, L2-5

Böhme, FrankIL-1

Hayashi Yoshihiro

P37

Bryce, David L.

IL-2

Hibe Yuta

P71

Higashi Takanori

P88Y

C
Chiba Yuya

P37

Hirao Yuuka

P79

Colby, Ralph H.

IL-1

Hironishi Reika

P18Y

Coppel, Yannick

L1-6

Hirose Yuu

L2-1, P72

Hirotsu Naoki

P23

D
Döhler, Diana

IL-1

Hishikura Naoki

P63

Dokainish, Hisham

P68Y

Homma Michio

L2-3

Dwivedi-Agnihotri, Hemlata

L3-2

Hoshino Shin-ichi

L2-7

Hosoda Kazuo

P87

Hosoda Nao

L2-7

Hosoe Nanaka

P53

Hu, Zhiyan

P24Y, L5-1, L5-6, P28Y,

E
Enokizono Yoshiaki

L4-2
F

Fujikawa Kohki

L1-3－ 354 －P34Y
I

Kainosho Masatsune

P67, P68Y

Kaji Hironori

L5-4, P62Y, P76Y

Ichijo Rika

P2Y

Kambe Takashi

P76Y

Ida Tomonori

P19, P53

Kamei Shun

P74Y

Igarashi Shunsuke

P15

Kamide Tomoya

P21

Iizuka Tomona

P52Y

Kamihara Takayuki

P29, P47

Iizuka Yusuke

L2-1, P72

Kamimura Takashi

P2Y

Ikegami Takahisa

P73

Kamino Satoshi

L2-1

Ikeguchi Masamichi

P50Y

Kamoshida Hajime

P49

Ikeya Teppei

L5-7, P49, P55, P63, P67,

Kanaori Kenji

P39, P51

P68Y, P74Y

Kandori Hideki

P84Y

L2-7, L2-8, L4-1, P15,

Kanehashi Koji

P20Y

P66Y

Kaneko Shun

P66Y

Inamura Yuga

P33

kaneko sohei

P82Y

Inomata Kousuke

P49, P55, P63, P67, P68Y,

Kasai Takuma

L5-5, L5-7

P74Y, L4-2

Kasuya Naohiro

P51

Inukai Munehiro

L5-2, P80Y, P82Y

Katahira Masato

L2-2, P48Y

Ishida Yasuhiro

P32Y

Katayama Kota

P84Y

Ishihara Soma

P52Y

Kato Ken

P35, P77

Ishii Sakurako

P71

Katoh Etsuko

P23

Ishii Yoshitaka

L3-6, P29, P47, P57, P89,

Kawabata Natsuki

P4Y

P93

Kawabata Youhei

P68Y

Ishii Yuichiro

L2-7

Kawai Gota

P2Y, P3, P56Y

Ishizuki Kyoko

P40Y

Kawamura Izuru

P31, P84Y, P86Y

Isiguro Takaya

P47

Kawatsu Kosaku

P42Y

Itasaka Yuma

P32Y

Kay, Julie D.

L3-1

Ito Nobuyasu

P17Kay, Lewis E.

L3-1

Ito Yutaka

L2-1, P49, P55, P63, P67,

Kee, Li Bing

P29

P68Y, P74Y

Kigawa Takanori

L5-5, L5-7

Itoh-Watanabe Hikari

P31

Kikuchi Jun

P25, P36Y, P43, P58, P59,

Iwai Kazuhiro

P30

Imai Shunsuke

P69

J
Jiang, Jiaxi

Kikuchi Sho

L1-2, P90Y

P24Y, L5-1, L5-6, P28Y,

Kimura Tomomi

P42Y

P34Y

Kitagawa Masahiro

P70Y

Kitahara Ryo

L4-3, P60

K
Kadoma Hiroshi

L1-4

Kitamaki Yuko

P17

Kagawa Akinori

P70Y, P80Y

Kitayama Syoya

P58

Kahn, Myrtil L.

L1-6

Kitazawa Soichiro

L4-3, P60

－ 355 －

Kobayashi Fumiya

P81

Matsumoto Tomoko

P43

Kobayashi Naohiro

L3-6, P61, P73

Matsunaga Itta

P69

Kodama S Takashi

L4-2

Matsunaga Tatsuya

L3-6, P29, P89

Kofuku Yutaka

L2-8, L3-2, L4-1, P15,

Mikage Shohei

P38Y

P66Y

Mikawa Tsutomu

P49, P67, P68Y, P74Y

Kohda Daisuke

L2-5, P64Y

Mineshige Atsushi

L5-3

Kohn, Benjamin

L2-6

Mio Kazuhiro

P75

Kohno Toshiyuki

P1

Mishima Masaki

L2-1, P6Y, P63, P67, P68Y,

Koide Reina

P60

Kojima Chojiro

L4-2, P14Y, P32Y, P61

Miyanishi Koichiro

P80Y

Kojima Keiichi

P18Y

Miyanoiri Yohei

L2-1, L2-3, L4-3, P68Y

Kojima Seiji

L2-3

Miyata Hiroki

P74Y

Kokago Aoi

P32Y

Mizukoshi Toshimi

P15

Kon Yoshihiro

L1-6

Mizumura Takuya

L2-8

Kondo Keiko

L2-2

Mizuno Motohiro

L5-2, P19, P53, P81, P82Y,

Konuma Tsuyoshi

P73

Koteishi Hiroyasu

P63

Mochizuki Yuki

P70Y

Kumada Shungo

P37

Mohanty, Biswaranjan

L4-3

Kumagai Sari

P84Y

Monden Noriko

L4-2

Kumaki Yasuhiro

L5-1, L5-6, P24Y, P28Y,

Monobe Yoko

L4-2

P33, P34Y, P52Y

Mordvinkin, Anton

IL-1

P24Y, L5-6, P28Y, P34Y,

Mori Shoko

L1-3

P52Y

Morimoto Daichi

AL-2, L2-6, P30, P54Y,

Kumeta Hiroyuki

P72

P85

Kurihara Takuya

L5-2, P19, P53, P81, P82Y

Kurita Junichi

P79

Morinaga Takashi

P88Y

Kurita Masatoshi

L2-8

Morooka Hitoshi

P27

Kusumi Ryosuke

L1-4

Murakami Masato

P90Y, L1-2

Kusunoki Hideki

P1

Murakami Miwa

L5-3

Kuwahara Daisuke

P65

Kuwayama Tomoya

P42Y

N

L
Lafon, Olivier

P83

L1-6
M

Nagae Takayuki

L2-1, P6Y, P72

Nagahama Tomomi

P46Y

Nagashima Hiroki

L1-6

Nagashima Toshio

P18Y, P84Y

Maruhashi Aimi

P59

Nagata Takashi

L2-2, P1, P48Y,

Masubuchi Yuji

P71

Nagatoishi Satoru

P23

Matsuda Isamu

L3-6, P29, P47, P57

Naito Akira

P31

Matsuki Yoh

L1-5, P10Y, P35, P45, P77

Nakagawa Naoya

P65

Matsukuma Shinya

P40Y

Nakajima Hiroki

P6Y－ 356 －

Nakajima Yurie

P52Y

Omar, Eladl

L2-2

Nakamura Kiminori

P24Y

Onuki Yoshinori

P37

Nakamura Koichi

P80Y, P82Y

Osada Seiji

P24Y, L5-6, P28Y, P34Y

Nakamura Misaki

L4-2

Osawa Masanori

L2-7, P42Y

Nakamura Risa

P42Y

Osawa Tsukiho

L1-3

Nakamura Satoe

P17

Otsuka Yusuke

P27

Nakamura Takashi

L1-2, P90Y

Oyadomari Ryo

P47

Nakashima Yoshito

P5

Nakatani Kazuhiko

P14Y

Pandey, Shubhi

L3-2

Nakatsuka Shoichi

P42Y

Patchiya, Phanthong

P16

Nakazawa Chikako

P38Y

Namiki Tomoya

P81

Rangadurai, Atul Kaushik

L3-1

Namsrai, Javkhlantugs

P31

Ren, Weitong

P68Y

Negoro Makoto

P70Y, P80Y

Rioual, Elisa

L5-7

Nishikino Tatsuro

L2-3

Nishimura Yoshifumi

P79

Saalwächter, Kay

IL-1

Nishina Yuta

P76Y

Sagae Takeru

L2-7

Nishiyama Ken-ichi

L1-3

Saito Akira

P81

Nishiyama Yusuke

L3-4, P26Y, P80Y

Saito Jun

P42Y

Nishizaki Yuzo

P40Y

Saito Koji

P20Y

Nishizawa Mayu

L2-6

Saito Naoki

P9, P13

Noda Yasuto

P71

Sakai Naomichi

L1-2, P90Y

Nomrua Kaoru

L1-3

Sakakura Masayoshi

P75

Norinaga Koyo

P20Y

Sakamoto Taiichi

P1, P6Y, P46Y

Sakamoto Tomoki

L2-2, P48Y

P

R

S

O
Obana Shunichi

P81

Sakata Kenji

P59, P69

Ogaeri Yutaro

P26Y

Sakurabayashi Shuhei

P14Y

Ogura Tatsuki

P12

Sasahara Hisamu

P62Y

Ohnishi Yuki

P24Y, L5-1, L5-6, P28Y,

Sasakawa Hiroaki

P44Y

P33, P34Y

Sato Haruki

P80Y

Oide Mao

P68Y

Sato Riho

P43

Oka Tetsuo

L1-2, P90Y

Satoh Ryo

P88Y

Okada Kotaro

P37

Satoh Takehiro

P88Y

Okamrura Hideyasu

P86Y, P88Y

Sawada Haruka

P11

Okamura Satoru

P62Y

Sawai Hitomi

P63

OKAMURA Tetsuji

L1-2, P7, P22Y, P90Y

Sawazaki Ryoichi

L2-7

Okubo Rika

P63

Saya Hideyuki

P42Y

Okushita KeikoP20Y

Scanlon, Martin

L4-3－ 357 －

Scheler, Ulrich

L2-6

Suzuki Takumi

P6Y

Senda Toshiya

P42Y

Suzuki Yu

P86Y, P88Y

Shigemitsu Yoshiki

P29, P57, L3-6

Suzuki Yuto

P86Y

Shigeta Yasuhiro

P19, P53, P85

Shikata Ayumi

P78Y

Tabata Maako

P67, P68Y

Shima Kaito

P55

Tadokoro Makoto

P81

Shimada Ichio

L2-7, L2-8, L3-2, L3-3,

Tagami Osamu

P78Y

L4-1, P15, P66Y

Tagishi Ryouma

P49

Shimamoto Keiko

L1-3

Takahashi Hideo

P18Y

Shimizu Yoshitaka

P17

Takahashi Masakuni

P78Y

Shinagawa Hideyuki

P78Y

TAKAHASHI Masato

P7, P22Y, P90Y, L1-2

Shinki Souta

P71

Takahashi Sayaka

P87

Shiraishi Yutaro

L2-8, L3-2, L4-1, P15

Takahashi Seizo

P3

Shirakawa Masahiro

L2-6, L4-2, P30, P83

Takahashi Takafumi

P20Y, P27

Shiro Yoshitsugu

P63

Takamatsu Kyosuke

L2-4

Shukla, Arun K.

L3-2

Takaya Nobuhiro

P13

Someya Tatsuhiko

P46Y

Takeda Kazuyuki

L1-1, L1-4, P8Y, P11, P21,

Song Zihao

L5-1, L5-6, P24Y, P28Y,

T

P94Y

P33, P34Y

Takegoshi Kiyonori

HL-1, P71

Sorada Tomoki

P54Y

Takeuchi Koh

L2-8, L3-3

Souri Yue

P19

Tamaki Hajime

P35, P45, P77, P92Y

Suckow, Marcus

IL-1

Tanabe Mikio

P42Y, P75

Sudo Yuki

P18Y

Tanaka Kayoko

P74Y

Suehiro Shiori

P55

Tanaka Shinji

P16

Suematsu Takako

P40Y

Tateno Keita

P67, P68Y

Sugasawa Haruka

P67, P68Y, P74Y

Tehrani, Mohammad Jafar

L3-6

Sugase Kenji

L2-6, P30, P54Y, P83

Terami Hibiki

P57, L3-6

Sugiki Toshihiko

L4-2, P32Y

Teramura Takuo

P39

Sugimoto Naoki

P40Y

Teranishi Takashi

P78Y

Sugishita Tomoaki

P35, P77

Terao Takeshi

P91

Sugita Tomoko

P16

Terauchi Tsutomu

P68Y

Sugita Yuji

P67, P68Y

Terayama Kei

P59

Suzuki Ei-ichiro

P15

Tjandra, Nico

IL-3

Suzuki Furitsu

P62Y

Tochio Hidehito

L4-2

Suzuki Katsuaki

L5-4, P62Y, P76Y

Togashi Naoyuki

P74Y

Suzuki Rika

P18Y

Togawa Wataru

P61

Suzuki Shibuki

P84Y

Tokuda Norihiro

L2-4

Suzuki Takafumi

P55

Tomemori Megumi

P56Y－ 358 －

Tominaga Yusuke

L1-1

Yamaguchi Hideyuki

P15

Toyama Yuki

L3-1

Yamaguchi Makoto

P91

Toyoda Mei

P55

Yamamoto Junya

L4-3, P60

Toyoda Shuhei

P31

YAMAMOTO Kouki

P7, P22Y

Trebosc, Julien

L1-6

Yamamoto Kyoka

P51

Tritrakarn, Techit

P7, P22Y, L1-2, P90Y

Yamamoto Masayuki

P55

Tsuboi Yuuri

P36Y, P58

Yamaoki Yudai

L2-2, P48Y

Tsuchida Tomoki

L2-8

Yamauchi Kazuo

L5-1, L5-6, P24Y, P28Y,

Tsumoto Kouhei

P23

P34Y

U

Yamazaki Taichi

P17

Uchida Noriyuki

P32Y

Yamazaki Toshio

P18Y, P73, P84Y

Ueda Kazuyoshi

P31

Yanagida Yuki

P50Y

Ueda Takumi

L3-2, AL-1, L2-8, L4-1,

Yanagisawa Kota

P6Y

P66Y

Yao Shigeru

P16

Ute Koichi

L2-4

Yasui Hayate

L1-4

Utsumi Hiroaki

P44Y

Yokogawa Mariko

L2-7, P42Y

Yokomizo Tomoki

P15, L4-1

W
Wada Masahisa

L1-4

Yokoyama Daiki

P58, P59

Wakamatsu Kaori

HL-2, P1, P32Y

Yokoyama Kazuya

L1-2, P90Y

Wakamoto Takuro

P60

Yoshida Kiyomi

P50Y

Wakayama Masataka

P12

Yoshikawa Ichiho

P52Y

Walinda, Erik

P30, P54Y, P83, L2-6

Yoshimizu Hiroaki

P41

Wang, Yu

P8Y

Yoshimura Hironobu

P40Y

Watanabe Hidehiro

P13

Watanabe Kazuya

L2-4

Zhang, Xin

P92Y

Watanabe Riki

P63

Zhang, Zhongliang

P10Y

Watanabe Soh

L2-4

Zheng, Jingkang

P52Y

Weiming, Jiang

P94Y

Wickramasinghe, Ayesha

P93, L3-6

Z

X
Xiao, Yiling

P93

Xue, Xianyu

L3-5
Y

Yabu Yoshihiro

P49

Yagi Hiromasa

L5-7

Yagi Tatsunori

P69

Yamada Shunji

P25, P36Y, P43

Yamada Takeshi

P14Y－ 359 －

Ascend Evo 1 GHz Magnet• ‫ڽ‬ҡద͵ξΤϱγ΢ζϱήᩥ❶• ӹର+HভඇྖΝˍఁ‫ݰ‬• ৿અ‫ܯ‬.Ϝήϋρφ

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Innovation with Integrity

NMR߻੔֮೟ɼߑଆմੵ
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଎ఈ͗؈ୱʀʹ͵ͪͲ΍ͤ͛Ͷ͓࢘Ζ*R6FDQλϓφΤΥΠ

ԿָࣞͳηϘέφϩΝ༽͏ͪߑଆࣞ͹‫ࢋܯ‬ʀௗ೧͹ࣰ੹ͳ৶བ͹7RS6SLQλϓφΤΥΠ
ʀ0QRYDͳ͹࿊‫ܠ‬؈ୱ͵͹Ͷɼ͠ΔͶʀʀʀʀ್࣏‫ݫ‬ηϘέφϩ଎ఈΉͲՆ೵ʀ‫ؽ‬փָस͹Ғ૮ึਜ਼ͳϗʖηϧ΢ϱึਜ਼ʀʛˈ͹൥ҕͲԻౕઅఈՆ೵
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3$/ΨʖφγϱϕϩοΥϱζϡʖ

Innovation with
Integrity

NMR᳗⇺⇹⇾᷺Ḍ᷸ᷦᷫ᷌᲼ḃ᳘ᶟ͚ᵼ‫׷‬ᶞՎѴͽଷРୟᶞ‫ڿ‬इਘᶚʕ‫ڿ‬Ღଷਦᶛ‫ם‬Սᶉᶻᶃᶘ᷂೜‫ښ‬ᶇᲢ‫׷‬મഋ࠮ᶞࢀ८ਘᶚ⇺⇹⇾ՎѴ‫ࡷڞ‬Ღࡷ୿᷂ഋᶉᶻᴻЯЈᶗᷰᷦᷫḒ᲼᷂᷒‫׃‬঍ᶇᶖᵴᶮᶉᲣ
ᴷᶔᶞ⇺⇹⇾Ј඼ЛҴᶛᶲҔඋᵴᶏᶐᵽᲢࢀ८ਘᶚ⇺⇹⇾ࡷ୿ᶘЈ඼щ‫ݏ‬᷂௣ֳᵴ௰೮ᶞ‫ټ‬ΪϡՎѴ۴ᶛतᶇᶖਃҍᶇᶖᵴᶮᶉᲣૈ‫ ۀ‬Ყ ⇝⇝Ը⇞⇤ૈ⇔Ը⇕⇌⇝⇟⇦⇜⇜᳁⇝⇣⇦⇜⇜߈‫ ݨ‬Ყ ⇭⇼տᷱ೧᳉ਗ਼Ҍੂ‫ׇ‬Ӕ᳊᷍ḖḌ᷇Ḗ੽‫ۀ‬ଅߨ޸‫ؽ‬ᶟᶃᶑᶹ

KWWSVQPUSIMS高 性 能 卓 上 型 NMR‫ך׉‬䚍腉‫כ‬ծչ⼾♳㘗պ‫ך‬嚊䙀‫׾‬㢌ִ‫׷‬կ‫ٔء‬٦‫♳〷ؤ‬剑넝‫ך‬䠬䏝‫ה‬㢳圫䚍

Spinsolve 90‫ٔء‬٦‫ؤ‬剑넝‫ ؙحلأ‬90MHz ‫ ך‬NMR

Spinsolve Multi-Xⱄ‫ُث‬٦‫ص‬ٝ‫♶ؚ‬銲‫ד‬4 呌珏庠㹀〳腉˟ֿ‫ך׵׍‬醡ㅷ‫כ‬䋆劣‫ך‬醡ㅷ‫لس؎ؖ‬٦‫׮חآ‬䲓鯹ׁ‫ׅתְג׸‬կ⯓鹌涸‫♳⼾ז‬㘗 NMR

չSpinsolveպ嵲㢩✲噟鿇խ嵲㢩✲噟铬
տ103-0023 匌❨鿪⚥㣛⼒傈劤堀劤歕 2-8-8㸘峸Ⱏ司‫ٕؽ‬F

٥宕⛉煁瀖‫׾‬欽ְ‫♳⼾׋‬㘗NMR ⴓ⯔鎘٥庠㹀呌珏1H, 19F, 13C, 31P, ‫➭ך׉‬٥‫؝‬ٝ‫דزؙػ‬知⽃乼⡲٥ٔ،‫ّءؙ‬ٌٝ‫ٔةص‬ٝ‫ؚ‬〳腉٥鸐䌢‫نٓך‬橆㞮‫ד‬⢪欽〳腉

٥2Dָ庠㹀〳腉٥Ⲇ⽱徇㯭ָ♶銲٥⡚ٓٝ‫ص‬ٝ‫زأ؝ؚ‬٥荈⹛‫يء‬锃侭〳腉٥⯍㹋‫؎ٓך‬ٝ‫فحش‬60, 80, 90MHz, Ultra

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TEL03-3527-2745

https://dsd.nakayama-co.jp

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➂䕎歕‫ٕؽ‬寐䨫㾊‫ـإ‬ٝ؎ٖ‫ـ‬ٝ

Daiichi Sankyo⚥㿊㉀✲ 匌❨‫ٌٕر‬٦‫ي‬㸘峸Ⱏ司‫ٕؽ‬F‫ؿ‬؋‫ٔى‬٦‫و‬٦‫ز‬

NMRЎௌỉỼὅἼὊὁὅὉἏἧἚ
:LQGRZVӻӺՒӻӻ ໴ࣤᄟՒӻӻӨ ӨԝԚԡ ‫ח‬،‫צ؟‬՛‫ب؜׬‬Ք‫ײ‬؊‫ ׽‬ԋԙԔԍԏ ‫؟׬‬՛‫ׯ‬๔ዿ‫׼‬՛‫״‬Ք؎՛‫׮‬À ԐԔԎ ‫׼‬՛‫ ֧״‬ԋԙԔԍԏ ‫׼‬՛‫ב״‬؋‫׫כ؞‬එ֦ࡴউ৉ጫÀ ‫ؠץ‬՛،ၾ੢ዛँ‫ ב‬ԋԙԔԍԏ ‫׼‬՛‫؎״‬՛‫֦׮‬ಲଵఇࡸ˟ᅈἢỶỼ἟ἕἚᄂᆮ৑

։ኴ஽֚‫ב‬։໸֖֥֠։‫ֽ֘׉‬ԺՂԶՃԊԲԺՃӷՂԵՈӸԳՃӸԻՄ

https://bionet.co.jp/大陽日酸は多次元NMRでの構造解析に必須な安定同位体標識化合物を高品質
元NMRでの構造解析に必須なな安定同位体標識化合物を高品質・お求め易い価格で販売しております。
お求め易い価格で格で販
格で販売

無細胞タンパク質受託合成
細胞内タンパク質、分泌系タンパク質、膜タンパク質合成を承ります。
弊社HPの専用フォームより簡単にご依頼いただけます。
■ 鋳型DNA設計・作製■ 発現・可溶性確認試験■ 条件検討試験■ 大スケール合成

無細胞くん®
理化学研究所の高度な無細胞タンパク質合成技術をキット化いたしました。大腸菌抽出液を用いており、抗体や膜タンパク質などをはじめ各種タ
ンパク質を迅速・簡便に大量合成し、高効率に安定同位体標識できます。

製品番号■ 無細胞くんStart特徴
無細胞タンパク質合成をお手軽にお試しいただけます 。小スケール（0.1mL）反応を付属の微量透析カップで6回実施できます。発現量や可溶性の確認および条件検討用に
最適です。

製品名

数量

保存温度 希望納入価格（円）

1キット
A183-0242 無細胞くんStart−80℃（0.1mL反応×6回分）

28,000

A89-0126 無細胞くんSI SS

1キット
−80℃
（1mL反応×1回分）

65,000

A29-0059

1キット−80℃（1mL反応×1回分）

55,000無細胞くんSI◎ PCRで調製した直鎖状DNAもご使用いただけます。
国立研究開発法人 科学技術振興機構「産学共同シーズイノベーション化事業」の支援を受け、開発された製品です。

無細胞くん用 安定同位体標識アミノ酸・膜タンパク質合成用試薬■SAIL メチル・芳香族選択標識
製品番号
SAT2001

製品名
SAIL アミノ酸混合物水溶液[δ2-13CH3;2H]Leu＋ [γ1-13CH3;2H]Val+ 18種重水素標識アミノ酸

G07-0226■膜タンパク質合成用試薬
数量 希望納入価格（円）1mL
220,000
1mL

120,000

膜タンパク質 発現例■各種安定同位体標識アミノ酸
製品番号
A107-0144
A39-0072
A41-0074
A40-0073
A42-0075
A91-0128
A92-0129
A108-0145

製品番号
製品名
数量 希望納入価格（円）A226-0290 膜タンパク質合成用添加剤 Set A 1キット
20,000Bacteriorhodopsin

製品名
数量 希望納入価格（円）
アミノ酸混合物水溶液-UL-d
1mL
25,0001mL
15,000アミノ酸混合物水溶液-UL-15N
1mL
18,000アミノ酸混合物水溶液-UL-15N,d
1mL
30,000アミノ酸混合物水溶液-UL-13C,15N
1mL
35,000アミノ酸混合物水溶液-UL-13C,15N,d
アミノ酸混合物水溶液-Lys,Arg-UL-13C,15N 1mL
20,000アミノ酸混合物水溶液-Lys,Leu-UL-13C,15N 1mL
20,000アミノ酸混合物水溶液-SeMet
1mL
12,00020種類のアミノ酸を含有しております。
Purplish brown color represents proper folding of Bacteriorhodopsin.

用途例◎ スクリーニング用多検体発現、細胞毒性タンパク質発現、変異体発現◎ 多次元NMR、クライオ電子顕微鏡、X線回折、中性子線回折等による構造解析用タンパク質発現◎ 質量分析用安定同位体標識タンパク質発現

核酸● 10%, 20% Phosphoramidites (13C, 15N, d)● NTPs / NMPs (13C, 15N, d) ● RNA・DNAオリゴマ合成

アミノ酸・ケト酸● L-Amino Acids (13C, 15N, d)●α-Keto Acids (13C, d)

その他

培地
13

15

● D-Glucose ( C, d) ● Salts ( N, d)● Deuterium Oxide 99.9atom%● Algal Amino Acids (13C, 15N, d)ing
ComSoon！Deuterated NDSB

● Water-17O (10-90atom%)● Lanthanide Tag● Pf1 NMR Cosolvent※Biomolecular NMR専門カタログをご用意しておりますのでお気軽にお問い合わせください。
製造・総販売元

大陽日酸株式会社 イノベーションユニット SI事業部

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